From 49a73549b91cc0a589d3a44e59dd4687e774d296 Mon Sep 17 00:00:00 2001 From: Jeff Rasley Date: Tue, 30 May 2023 12:07:31 -0700 Subject: [PATCH 01/32] AISC launcher fixes (#3637) * tmp remove launcher args * add exclude list for env variables on aisc * add comment --- deepspeed/launcher/runner.py | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/deepspeed/launcher/runner.py b/deepspeed/launcher/runner.py index 3bb41300de04e..c397cf48fbe2c 100755 --- a/deepspeed/launcher/runner.py +++ b/deepspeed/launcher/runner.py @@ -37,6 +37,10 @@ DEEPSPEED_ENVIRONMENT_PATHS = [os.path.expanduser("~"), '.'] PDSH_MAX_FAN_OUT = 1024 +# On AISC compute, each node sets environment variables independently, want to prevent +# exporting rank-0 env variables in case of heterogeneous compute. +EXCLUDE_ENVS = {'AISC_JOB_NAME': ['NCCL_IB_HCA', 'UCX_NET_DEVICES']} + def parse_args(args=None): parser = argparse.ArgumentParser(description="DeepSpeed runner to help launch distributed " @@ -523,10 +527,17 @@ def main(args=None): else: env['PYTHONPATH'] = curr_path + excluded_vars = [] + for exclude_key, var_list in EXCLUDE_ENVS.items(): + if exclude_key in env.keys(): + # key exists in launcher env -> var list should be used + excluded_vars += var_list + exports = "" for var in env.keys(): if any([var.startswith(name) for name in EXPORT_ENVS]): - runner.add_export(var, env[var]) + if not any([var == name for name in excluded_vars]): + runner.add_export(var, env[var]) for environ_path in DEEPSPEED_ENVIRONMENT_PATHS: environ_file = os.path.join(environ_path, DEEPSPEED_ENVIRONMENT_NAME) From 52907a661c558044a428eaf9e8a54331d862b5c2 Mon Sep 17 00:00:00 2001 From: Guo Yejun Date: Wed, 31 May 2023 04:54:05 +0800 Subject: [PATCH 02/32] stage3.py: do not scale if gradient_predivide_factor is 1.0 (#3630) this change also aligns with the logic before reduce_scatter_coalesced Co-authored-by: Olatunji Ruwase --- deepspeed/runtime/zero/stage3.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/deepspeed/runtime/zero/stage3.py b/deepspeed/runtime/zero/stage3.py index 290ee75e6613e..b23f5d089c859 100644 --- a/deepspeed/runtime/zero/stage3.py +++ b/deepspeed/runtime/zero/stage3.py @@ -1122,7 +1122,8 @@ def __avg_scatter_grads(self, params_to_reduce: List[Parameter]) -> List[Tensor] grad_partitions_for_rank = reduce_scatter_coalesced(full_grads_for_rank, self.dp_process_group) - if self.postscale_gradients and self.gradient_predivide_factor != dist.get_world_size(self.dp_process_group): + if self.postscale_gradients and self.gradient_predivide_factor != 1.0 and self.gradient_predivide_factor != dist.get_world_size( + self.dp_process_group): grad_partitions_for_rank = [g.mul(self.gradient_predivide_factor) for g in grad_partitions_for_rank] if self.communication_data_type != self.dtype: From f3c8eacafc5f3061b67e2db1f98aba319b378eb5 Mon Sep 17 00:00:00 2001 From: CurryRice233 Date: Wed, 31 May 2023 22:24:24 +0800 Subject: [PATCH 03/32] Add Ascend NPU accelerator support (#3595) * add Ascend NPU accelerator support * clean code --------- Co-authored-by: jializheng Co-authored-by: Olatunji Ruwase --- accelerator/npu_accelerator.py | 241 +++++++++++++++++++++++++++++++++ 1 file changed, 241 insertions(+) create mode 100644 accelerator/npu_accelerator.py diff --git a/accelerator/npu_accelerator.py b/accelerator/npu_accelerator.py new file mode 100644 index 0000000000000..a92cb0f770852 --- /dev/null +++ b/accelerator/npu_accelerator.py @@ -0,0 +1,241 @@ +# Copyright (c) Microsoft Corporation. +# SPDX-License-Identifier: Apache-2.0 + +# DeepSpeed Team + +from .abstract_accelerator import DeepSpeedAccelerator +# During setup stage torch may not be installed, pass on no torch will +# allow op builder related API to be executed. +try: + import torch.npu +except ImportError: + pass + + +class NPU_Accelerator(DeepSpeedAccelerator): + + def __init__(self): + self._name = 'npu' + self._communication_backend_name = 'hccl' + + def is_synchronized_device(self): + return False + + # Device APIs + def device_name(self, device_index=None): + if device_index == None: + return 'npu' + return 'npu:{}'.format(device_index) + + def device(self, device_index=None): + return torch.npu.device(device_index) + + def set_device(self, device_index): + torch.npu.set_device(device_index) + + def current_device(self): + return torch.npu.current_device() + + def current_device_name(self): + return 'npu:{}'.format(torch.npu.current_device()) + + def device_count(self): + return torch.npu.device_count() + + def synchronize(self, device_index=None): + return torch.npu.synchronize(device_index) + + # RNG APIs + def random(self): + return torch.random + + def set_rng_state(self, new_state, device_index=None): + if device_index is None: + return torch.npu.set_rng_state(new_state) + + return torch.npu.set_rng_state(new_state, device_index) + + def get_rng_state(self, device_index=None): + if device_index is None: + return torch.npu.get_rng_state() + + return torch.npu.get_rng_state(device_index) + + def manual_seed(self, seed): + return torch.npu.manual_seed(seed) + + def manual_seed_all(self, seed): + return torch.npu.manual_seed_all(seed) + + def initial_seed(self, seed): + return torch.npu.initial_seed(seed) + + def default_generator(self, device_index): + return torch.npu.default_generators[device_index] + + # Streams/Events + @property + def Stream(self): + return torch.npu.Stream + + def stream(self, stream): + return torch.npu.stream(stream) + + def current_stream(self, device_index=None): + return torch.npu.current_stream(device_index) + + def default_stream(self, device_index=None): + return torch.npu.default_stream(device_index) + + @property + def Event(self): + return torch.npu.Event + + # Memory management + def empty_cache(self): + return torch.npu.empty_cache() + + def memory_allocated(self, device_index=None): + return torch.npu.memory_allocated(device_index) + + def max_memory_allocated(self, device_index=None): + return torch.npu.max_memory_allocated(device_index) + + def reset_max_memory_allocated(self, device_index=None): + return torch.npu.reset_max_memory_allocated(device_index) + + def memory_cached(self, device_index=None): + return torch.npu.memory_cached(device_index) + + def max_memory_cached(self, device_index=None): + return torch.npu.max_memory_cached(device_index) + + def reset_max_memory_cached(self, device_index=None): + return torch.npu.reset_max_memory_cached(device_index) + + def memory_stats(self, device_index=None): + if hasattr(torch.npu, 'memory_stats'): + return torch.npu.memory_stats(device_index) + + def reset_peak_memory_stats(self, device_index=None): + if hasattr(torch.npu, 'reset_peak_memory_stats'): + return torch.npu.reset_peak_memory_stats(device_index) + + def memory_reserved(self, device_index=None): + if hasattr(torch.npu, 'memory_reserved'): + return torch.npu.memory_reserved(device_index) + + def max_memory_reserved(self, device_index=None): + if hasattr(torch.npu, 'max_memory_reserved'): + return torch.npu.max_memory_reserved(device_index) + + def total_memory(self, device_index=None): + return torch.npu.get_device_properties(device_index).total_memory + + # Data types + def is_bf16_supported(self): + return torch.npu.is_bf16_supported() + + def is_fp16_supported(self): + return True + + # Misc + def amp(self): + if hasattr(torch.npu, 'amp'): + return torch.npu.amp + return None + + def is_available(self): + return torch.npu.is_available() + + def range_push(self, msg): + return + + def range_pop(self): + return + + def lazy_call(self, callback): + return torch.npu._lazy_call(callback) + + def communication_backend_name(self): + return self._communication_backend_name + + # Tensor operations + + @property + def BFloat16Tensor(self): + return torch.npu.BFloat16Tensor + + @property + def ByteTensor(self): + return torch.npu.ByteTensor + + @property + def DoubleTensor(self): + return torch.npu.DoubleTensor + + @property + def FloatTensor(self): + return torch.npu.FloatTensor + + @property + def HalfTensor(self): + return torch.npu.HalfTensor + + @property + def IntTensor(self): + return torch.npu.IntTensor + + @property + def LongTensor(self): + return torch.npu.LongTensor + + def pin_memory(self, tensor): + return tensor.pin_memory() + + def on_accelerator(self, tensor): + device_str = str(tensor.device) + if device_str.startswith('npu:'): + return True + else: + return False + + def op_builder_dir(self): + try: + # is op_builder from deepspeed or a 3p version? this should only succeed if it's deepspeed + # if successful this also means we're doing a local install and not JIT compile path + from op_builder import __deepspeed__ # noqa: F401 + return "op_builder.npu" + except ImportError: + return "deepspeed.ops.op_builder.npu" + + # dict that holds class name <--> class type mapping i.e. + # 'AsyncIOBuilder': + # this dict will be filled at init stage + class_dict = None + + def _lazy_init_class_dict(self): + if self.class_dict != None: + return + else: + self.class_dict = {} + + # create an instance of op builder and return, name specified by class_name + def create_op_builder(self, class_name): + self._lazy_init_class_dict() + if class_name in self.class_dict: + return self.class_dict[class_name]() + else: + return None + + # return an op builder class, name specified by class_name + def get_op_builder(self, class_name): + self._lazy_init_class_dict() + if class_name in self.class_dict: + return self.class_dict[class_name] + else: + return None + + def build_extension(self): + from torch.utils.cpp_extension import BuildExtension + return BuildExtension From 8b8c7031fb9b3530fea0ede2c869e9099864e49a Mon Sep 17 00:00:00 2001 From: Michael Wyatt Date: Wed, 31 May 2023 10:53:31 -0700 Subject: [PATCH 04/32] Skip tests on docs-only changes (#3651) * skip test for docs-only changes * add missing skip to blog changes --- .github/workflows/cpu-inference.yml | 2 ++ .github/workflows/nv-pre-compile-ops.yml | 6 ++++++ .github/workflows/python.yml | 6 ++++++ 3 files changed, 14 insertions(+) diff --git a/.github/workflows/cpu-inference.yml b/.github/workflows/cpu-inference.yml index 7949f4af7c409..f139d84ee6e9d 100644 --- a/.github/workflows/cpu-inference.yml +++ b/.github/workflows/cpu-inference.yml @@ -6,9 +6,11 @@ on: - 'staging**' paths-ignore: - 'docs/**' + - 'blogs/**' pull_request: paths-ignore: - 'docs/**' + - 'blogs/**' concurrency: group: ${{ github.workflow }}-${{ github.ref }} diff --git a/.github/workflows/nv-pre-compile-ops.yml b/.github/workflows/nv-pre-compile-ops.yml index 2131fc4f94535..822ba2dea6053 100644 --- a/.github/workflows/nv-pre-compile-ops.yml +++ b/.github/workflows/nv-pre-compile-ops.yml @@ -4,9 +4,15 @@ on: push: branches: - 'staging**' + paths-ignore: + - 'docs/**' + - 'blogs/**' pull_request: branches: '**' + paths-ignore: + - 'docs/**' + - 'blogs/**' schedule: - cron: "0 0 * * *" diff --git a/.github/workflows/python.yml b/.github/workflows/python.yml index 60bebc44e8865..665d601bee6ed 100644 --- a/.github/workflows/python.yml +++ b/.github/workflows/python.yml @@ -4,9 +4,15 @@ on: push: branches: - 'staging**' + paths-ignore: + - 'docs/**' + - 'blogs/**' pull_request: branches: '**' + paths-ignore: + - 'docs/**' + - 'blogs/**' schedule: - cron: "0 0 * * *" From 8f459c50e79528eb2a2612f3a1ea280af6afe883 Mon Sep 17 00:00:00 2001 From: Will Jessup Date: Wed, 31 May 2023 13:53:57 -0400 Subject: [PATCH 05/32] Update megatron.md (#3641) grammar fix. Co-authored-by: Michael Wyatt --- docs/_tutorials/megatron.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/_tutorials/megatron.md b/docs/_tutorials/megatron.md index 0ccfd3ec02f13..5242c8184db8d 100644 --- a/docs/_tutorials/megatron.md +++ b/docs/_tutorials/megatron.md @@ -53,7 +53,7 @@ To use DeepSpeed we will modify three files : ### Argument Parsing -The first step is to apply DeepSpeed is adding DeepSpeed arguments to +The first step is adding DeepSpeed arguments to Megatron-LM GPT2 model, using `deepspeed.add_config_arguments()` in `arguments.py`. From e02b8d0bd06fd5e3d65c4bc410708ee2443334c7 Mon Sep 17 00:00:00 2001 From: Micah Zoltu Date: Thu, 1 Jun 2023 02:00:57 +0800 Subject: [PATCH 06/32] Typo Correction (#3621) Code (in this context) is mass noun, and thus has no plural form. Co-authored-by: Michael Wyatt --- docs/_pages/training.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/_pages/training.md b/docs/_pages/training.md index 9c95fa7857ca4..e31651cc487a7 100644 --- a/docs/_pages/training.md +++ b/docs/_pages/training.md @@ -44,7 +44,7 @@ optimizations on advanced hyperparameter tuning and optimizers. For example: | 64 V100 GPUs | DeepSpeed | **8.68** hr| | 16 V100 GPUs | DeepSpeed | **33.22** hr| - *BERT codes and tutorials will be available soon.* + *BERT code and tutorials will be available soon.* * DeepSpeed trains GPT2 (1.5 billion parameters) 3.75x faster than state-of-art, NVIDIA Megatron on Azure GPUs. From 3b299997610e4a93a506bc617584f2845a2051ea Mon Sep 17 00:00:00 2001 From: Guo Yejun Date: Fri, 2 Jun 2023 00:02:17 +0800 Subject: [PATCH 07/32] deepspeed/comm/comm.py: fix typo of warning message (#3636) Co-authored-by: Michael Wyatt --- deepspeed/comm/comm.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepspeed/comm/comm.py b/deepspeed/comm/comm.py index 4a9b51b9e6017..65070d83d3bb9 100644 --- a/deepspeed/comm/comm.py +++ b/deepspeed/comm/comm.py @@ -256,7 +256,7 @@ def reduce_scatter_fn(output_tensor, else: if get_rank() == 0: utils.logger.warning_once("unable to find torch.distributed.reduce_scatter_tensor. will fall back to " - "torch.distributed.all_gather which will result in suboptimal performance. " + "torch.distributed.reduce_scatter which will result in suboptimal performance. " "please consider upgrading your pytorch installation.") input_tensor_lst = list(torch.chunk(tensor, cdb.get_world_size(group))) return reduce_scatter(output_tensor, From f5dde36c1af9fe6b166ed05d381f546f53dcebce Mon Sep 17 00:00:00 2001 From: Haodong Lyu Date: Fri, 2 Jun 2023 02:40:36 +0800 Subject: [PATCH 08/32] Fix RuntimeError when using ZeRO Stage3 with mpu: #3564 (#3565) Co-authored-by: Olatunji Ruwase --- deepspeed/runtime/zero/stage3.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/deepspeed/runtime/zero/stage3.py b/deepspeed/runtime/zero/stage3.py index b23f5d089c859..5918fe25d74e3 100644 --- a/deepspeed/runtime/zero/stage3.py +++ b/deepspeed/runtime/zero/stage3.py @@ -1499,7 +1499,12 @@ def get_grad_norm_direct(self, gradients, params, norm_type=2): grad_norms.append(g.to(get_accelerator().device_name(), non_blocking=True).double().norm(2)) # Sum across all model parallel GPUs. - total_norm_cuda = torch.sum(torch.pow(torch.stack(grad_norms), 2)) + if len(grad_norms) == 0: + # FIX https://github.com/microsoft/DeepSpeed/issues/3564 + total_norm_cuda = torch.tensor(0, + dtype=gradients[0].dtype).to(get_accelerator().device_name()).double() + else: + total_norm_cuda = torch.sum(torch.pow(torch.stack(grad_norms), 2)) dist.all_reduce(total_norm_cuda, op=dist.ReduceOp.SUM, group=self.dp_process_group) From da8f4e01b55acc71e3da21d8c9aadae3b3f950bb Mon Sep 17 00:00:00 2001 From: Michael Wyatt Date: Thu, 1 Jun 2023 15:01:01 -0700 Subject: [PATCH 09/32] allow dict datatype for checkpoints (#3007) Co-authored-by: Olatunji Ruwase --- deepspeed/inference/config.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepspeed/inference/config.py b/deepspeed/inference/config.py index 99b56d1ad30c1..3474578e6a118 100644 --- a/deepspeed/inference/config.py +++ b/deepspeed/inference/config.py @@ -184,7 +184,7 @@ class DeepSpeedInferenceConfig(DeepSpeedConfigModel): """ #todo: refactor the following 3 into the new checkpoint_config - checkpoint: str = None + checkpoint: Union[str, Dict] = None """ Path to deepspeed compatible checkpoint or path to JSON with load policy. """ From cd4e473ee613a3c5d0b70769c5ec19a7fc8a453b Mon Sep 17 00:00:00 2001 From: digger yu Date: Fri, 2 Jun 2023 08:47:14 +0800 Subject: [PATCH 10/32] fix typo with deepspeed/ (#3547) * fix spelling error with deepspeed/runtime/ * fix typo docs/ * fix typo in comments with deepspeed/ * fix typo deepspeed/ * Update constants.py Remove the space after nebula --------- Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com> Co-authored-by: Michael Wyatt --- deepspeed/autotuning/autotuner.py | 2 +- deepspeed/compression/compress.py | 4 ++-- deepspeed/nebula/constants.py | 4 ++-- deepspeed/runtime/checkpoint_engine/README.md | 2 +- deepspeed/runtime/checkpoint_engine/checkpoint_engine.py | 2 +- deepspeed/runtime/engine.py | 2 +- 6 files changed, 8 insertions(+), 8 deletions(-) diff --git a/deepspeed/autotuning/autotuner.py b/deepspeed/autotuning/autotuner.py index 73825a69f582c..4ea71d317f2b1 100755 --- a/deepspeed/autotuning/autotuner.py +++ b/deepspeed/autotuning/autotuner.py @@ -637,7 +637,7 @@ def tune_space(self, tuning_space, prev_max_mbs=0, prev_best_mbs=0, prev_best_me logger.info(f"End tuning for space: {tuning_space_name}") return max_micro_batch_size, best_mbs, best_metric_val - def get_plauteu_mbs(self, tuning_space_name): + def get_plateau_mbs(self, tuning_space_name): if tuning_space_name not in self.records: return 0 space_records = self.records[tuning_space_name] diff --git a/deepspeed/compression/compress.py b/deepspeed/compression/compress.py index 951ef1bb2da10..2f0e88beee21c 100644 --- a/deepspeed/compression/compress.py +++ b/deepspeed/compression/compress.py @@ -213,14 +213,14 @@ def student_initialization(student_model, teacher_model, deepspeed_config): Example 1: bert.encoder.layer, for BERT_base model's prefix name Example 2: transformer.h, for GPT-2 hugging face prefix name teacher_layer (`list of integers`) - The layer of teacher will be used for student's reinitializedion + The layer of teacher will be used for student's reinitialization Example 1: [1,3,5,7,9], means we want to matches the 2nd/4th/6th/8th/10th layer of teacher to the first 5 layers of student student_layer (`list` or None) The layer of student need to be re-initialized Example 1: None, means we want to reinitialize all the layers Example 1: [0,1,2,3,4], means we want to reinitialize the first 5 layers other_module_name (`list of string`) - The modules will be used for student's reinitializedion + The modules will be used for student's reinitialization Example 1: ['bert.pooler', 'bert.embeddings', 'classifier'], means we want to apply the weight in teacher's embedding/pooler/classier module to the student Example 2: ['transformer.w', 'transformer.ln_f', 'lm_head'], means we want to apply the weight in teacher's embedding layers module to the student Note that teacher_layer should matches student layer diff --git a/deepspeed/nebula/constants.py b/deepspeed/nebula/constants.py index 2bfcef7751456..9fa5769b55979 100644 --- a/deepspeed/nebula/constants.py +++ b/deepspeed/nebula/constants.py @@ -29,8 +29,8 @@ # There is a case where customer want to load the checkpoint saved # by raw torch. Because nebula cannot load torch checkpoint directly # as they have different folder structures to bring the gap for -# loading(the data are totally same in bytes for torch and nebula s -# aving). +# loading(the data are totally same in bytes for torch and nebula +# saving). # In this case, we must disable nebula load to use raw torch load. # Customer can just set NEBULA_ENABLE_NEBULA_LOAD to False. Then use # original way of deepspeed to load, i.e. set the value of "--load". diff --git a/deepspeed/runtime/checkpoint_engine/README.md b/deepspeed/runtime/checkpoint_engine/README.md index a19f54889802f..c2b7940a414a7 100644 --- a/deepspeed/runtime/checkpoint_engine/README.md +++ b/deepspeed/runtime/checkpoint_engine/README.md @@ -31,7 +31,7 @@ class CheckpointEngine(object): pass def commit(self, tag): - # to tell checkpoint services if all files are readys. + # to tell checkpoint services if all files are ready. pass ``` diff --git a/deepspeed/runtime/checkpoint_engine/checkpoint_engine.py b/deepspeed/runtime/checkpoint_engine/checkpoint_engine.py index 3f8978df03167..a341dffdf692c 100644 --- a/deepspeed/runtime/checkpoint_engine/checkpoint_engine.py +++ b/deepspeed/runtime/checkpoint_engine/checkpoint_engine.py @@ -26,5 +26,5 @@ def load(self, path: str, map_location=None): pass def commit(self, tag): - # to tell checkpoint services if all files are readys. + # to tell checkpoint services if all files are ready. pass diff --git a/deepspeed/runtime/engine.py b/deepspeed/runtime/engine.py index 93ab0bdefc91d..b638969755df9 100644 --- a/deepspeed/runtime/engine.py +++ b/deepspeed/runtime/engine.py @@ -1916,7 +1916,7 @@ def set_gradient_accumulation_boundary(self, is_boundary): """ Manually overrides the DeepSpeed engine's gradient accumulation boundary state, this is an optional feature and should be used with care. The state should be set before to the intended - value before each forward/backward. The final fordward/backward should have the + value before each forward/backward. The final forward/backward should have the boundary state set to True. This style allows client code to only call engine.step() once after all the gradient accumulation passes are complete. See example below: .. code-block:: python From 460bec4679fb460ccc24f915ea1674e89baf698d Mon Sep 17 00:00:00 2001 From: Guo Yejun Date: Fri, 2 Jun 2023 23:20:41 +0800 Subject: [PATCH 11/32] flops_profiler: add option recompute_fwd_factor for the case of activation recompute (#3362) When activation checkpointing is enabled, most of forward is re-computed, and so the FLOPS calculation should be updated with recompute_fwd_factor=1.0 I don't find a way to pass the option from model script to deepspeed engine, and so add option directly for flops_profiler. Co-authored-by: Cheng Li --- deepspeed/profiling/config.py | 4 ++++ deepspeed/profiling/constants.py | 4 ++++ deepspeed/profiling/flops_profiler/README.md | 1 + deepspeed/profiling/flops_profiler/profiler.py | 17 ++++++++++------- deepspeed/runtime/engine.py | 5 ++++- 5 files changed, 23 insertions(+), 8 deletions(-) diff --git a/deepspeed/profiling/config.py b/deepspeed/profiling/config.py index 7533fc299f0e1..e4f06630ea6f6 100644 --- a/deepspeed/profiling/config.py +++ b/deepspeed/profiling/config.py @@ -13,6 +13,7 @@ def __init__(self, param_dict): super(DeepSpeedFlopsProfilerConfig, self).__init__() self.enabled = None + self.recompute_fwd_factor = None self.profile_step = None self.module_depth = None self.top_modules = None @@ -27,6 +28,9 @@ def __init__(self, param_dict): def _initialize(self, flops_profiler_dict): self.enabled = get_scalar_param(flops_profiler_dict, FLOPS_PROFILER_ENABLED, FLOPS_PROFILER_ENABLED_DEFAULT) + self.recompute_fwd_factor = get_scalar_param(flops_profiler_dict, FLOPS_PROFILER_RECOMPUTE_FWD_FACTOR, + FLOPS_PROFILER_RECOMPUTE_FWD_FACTOR_DEFAULT) + self.profile_step = get_scalar_param(flops_profiler_dict, FLOPS_PROFILER_PROFILE_STEP, FLOPS_PROFILER_PROFILE_STEP_DEFAULT) diff --git a/deepspeed/profiling/constants.py b/deepspeed/profiling/constants.py index e16baea27dede..0374303d7d969 100644 --- a/deepspeed/profiling/constants.py +++ b/deepspeed/profiling/constants.py @@ -13,6 +13,7 @@ "session_params": { "flops_profiler": { "enabled": true, + "recompute_fwd_factor": 0.0, "profile_step": 1, "module_depth": -1, "top_modules": 3, @@ -27,6 +28,9 @@ FLOPS_PROFILER_ENABLED = "enabled" FLOPS_PROFILER_ENABLED_DEFAULT = False +FLOPS_PROFILER_RECOMPUTE_FWD_FACTOR = "recompute_fwd_factor" +FLOPS_PROFILER_RECOMPUTE_FWD_FACTOR_DEFAULT = 0.0 + FLOPS_PROFILER_PROFILE_STEP = "profile_step" FLOPS_PROFILER_PROFILE_STEP_DEFAULT = 1 diff --git a/deepspeed/profiling/flops_profiler/README.md b/deepspeed/profiling/flops_profiler/README.md index af23d56ee76ab..82011eb68568e 100644 --- a/deepspeed/profiling/flops_profiler/README.md +++ b/deepspeed/profiling/flops_profiler/README.md @@ -166,6 +166,7 @@ When using DeepSpeed for model training, the profiler can be configured in the d { "flops_profiler": { "enabled": true, + "recompute_fwd_factor": 0.0, "profile_step": 1, "module_depth": -1, "top_modules": 1, diff --git a/deepspeed/profiling/flops_profiler/profiler.py b/deepspeed/profiling/flops_profiler/profiler.py index f39f25ce87b1a..b7a6878f1e69b 100644 --- a/deepspeed/profiling/flops_profiler/profiler.py +++ b/deepspeed/profiling/flops_profiler/profiler.py @@ -57,9 +57,10 @@ class FlopsProfiler(object): object (torch.nn.Module): The PyTorch model to profile. """ - def __init__(self, model, ds_engine=None): + def __init__(self, model, ds_engine=None, recompute_fwd_factor=0.0): self.model = model self.ds_engine = ds_engine + self.recompute_fwd_factor = recompute_fwd_factor self.started = False self.func_patched = False @@ -301,20 +302,22 @@ def print_model_profile(self, profile_step=1, module_depth=-1, top_modules=1, de flops_to_string(total_flops / fwd_latency))) if self.ds_engine and self.ds_engine.wall_clock_breakdown(): + bwd_factor = 2 + self.recompute_fwd_factor bwd_latency = self.ds_engine.timers('backward').elapsed(False) / 1000.0 step_latency = self.ds_engine.timers('step').elapsed(False) / 1000.0 print('{:<60} {:<8}'.format('bwd latency: ', duration_to_string(bwd_latency))) - print('{:<60} {:<8}'.format('bwd FLOPS per GPU = 2 * fwd flops per GPU / bwd latency: ', - flops_to_string(2 * total_flops / bwd_latency))) - print('{:<60} {:<8}'.format('fwd+bwd FLOPS per GPU = 3 * fwd flops per GPU / (fwd+bwd latency): ', - flops_to_string(3 * total_flops / (fwd_latency + bwd_latency)))) + print('{:<60} {:<8}'.format(f'bwd FLOPS per GPU = {bwd_factor} * fwd flops per GPU / bwd latency: ', + flops_to_string(bwd_factor * total_flops / bwd_latency))) + print('{:<60} {:<8}'.format( + f'fwd+bwd FLOPS per GPU = {bwd_factor+1} * fwd flops per GPU / (fwd+bwd latency): ', + flops_to_string((bwd_factor + 1) * total_flops / (fwd_latency + bwd_latency)))) print('{:<60} {:<8}'.format('step latency: ', duration_to_string(step_latency))) iter_latency = fwd_latency + bwd_latency + step_latency print('{:<60} {:<8}'.format('iter latency: ', duration_to_string(iter_latency))) - print('{:<60} {:<8}'.format('FLOPS per GPU = 3 * fwd flops per GPU / iter latency: ', - flops_to_string(3 * total_flops / iter_latency))) + print('{:<60} {:<8}'.format(f'FLOPS per GPU = {bwd_factor+1} * fwd flops per GPU / iter latency: ', + flops_to_string((bwd_factor + 1) * total_flops / iter_latency))) samples_per_iter = self.ds_engine.train_micro_batch_size_per_gpu() * self.ds_engine.world_size print('{:<60} {:<8.2f}'.format('samples/second: ', samples_per_iter / iter_latency)) diff --git a/deepspeed/runtime/engine.py b/deepspeed/runtime/engine.py index b638969755df9..903da363ccf9d 100644 --- a/deepspeed/runtime/engine.py +++ b/deepspeed/runtime/engine.py @@ -282,7 +282,7 @@ def __init__( log_dist(f"DeepSpeed Flops Profiler Enabled: {self.flops_profiler_enabled()}", ranks=[0]) if self.flops_profiler_enabled(): - self.flops_profiler = FlopsProfiler(self.module, self) + self.flops_profiler = FlopsProfiler(self.module, self, self.flops_profiler_recompute_fwd_factor()) if training_data: self.training_dataloader = self.deepspeed_io(training_data) @@ -570,6 +570,9 @@ def wall_clock_breakdown(self): def flops_profiler_enabled(self): return self._config.flops_profiler_config.enabled or self.autotuning_enabled() + def flops_profiler_recompute_fwd_factor(self): + return self._config.flops_profiler_config.recompute_fwd_factor + def flops_profiler_profile_step(self): step = self._config.flops_profiler_config.profile_step if self._config.autotuning_config.enabled: From 5d14afd26ce89be4d4e6ebdf8fb6a943aebd4aa3 Mon Sep 17 00:00:00 2001 From: digger yu Date: Sat, 3 Jun 2023 01:51:04 +0800 Subject: [PATCH 12/32] fix typo deepspeed/runtime (#3663) Co-authored-by: Olatunji Ruwase --- deepspeed/runtime/zero/partition_parameters.py | 8 ++++---- deepspeed/runtime/zero/stage3.py | 4 ++-- deepspeed/runtime/zero/stage_1_and_2.py | 2 +- 3 files changed, 7 insertions(+), 7 deletions(-) diff --git a/deepspeed/runtime/zero/partition_parameters.py b/deepspeed/runtime/zero/partition_parameters.py index d4df1c4647467..db986c747970f 100755 --- a/deepspeed/runtime/zero/partition_parameters.py +++ b/deepspeed/runtime/zero/partition_parameters.py @@ -800,9 +800,9 @@ def _validate_remote_device(self, remote_device, ds_config): f'"nvme_path" in DeepSpeed Config cannot be None if remote device is {OffloadDeviceEnum.nvme}' def _post_init_method(self, module): - #see_memory_usage(f"Before converting parmas in {module.__class__.__name__}", force=False) + #see_memory_usage(f"Before converting params in {module.__class__.__name__}", force=False) print_rank_0(f'Converting Params in {module.__class__.__name__}', force=False) - see_memory_usage(f"Before converting and partitioning parmas in {module.__class__.__name__}", force=False) + see_memory_usage(f"Before converting and partitioning params in {module.__class__.__name__}", force=False) global param_count for name, param in module.named_parameters(recurse=False): @@ -825,7 +825,7 @@ def _post_init_method(self, module): param.partition() see_memory_usage( - f"Param count {param_count}. After converting and partitioning parmas in {module.__class__.__name__}", + f"Param count {param_count}. After converting and partitioning params in {module.__class__.__name__}", force=False) def _convert_to_deepspeed_param(self, param): @@ -1404,7 +1404,7 @@ def _reduce_scatter_gradients(self, param_list): partition_size = param.ds_tensor.ds_numel start = self.get_partition_rank() * partition_size end = start + partition_size - #print_rank_0("REduce scatter was executed for praam {param.ds_id}") + #print_rank_0("REduce scatter was executed for param {param.ds_id}") if start < param.ds_numel and end > param.ds_numel: elements = param.ds_numel - start param.grad.view(-1).narrow(0, start, elements).copy_(reduced_partition.narrow(0, 0, elements)) diff --git a/deepspeed/runtime/zero/stage3.py b/deepspeed/runtime/zero/stage3.py index 5918fe25d74e3..c5359a8272823 100644 --- a/deepspeed/runtime/zero/stage3.py +++ b/deepspeed/runtime/zero/stage3.py @@ -892,7 +892,7 @@ def initialize_optimizer_states(self): else: self.fp32_partitioned_groups_flat[i].grad = gradient_buffer.narrow(0, 0, num_elements) - # Initialize the optimizer states with the flattended fp32 partition. + # Initialize the optimizer states with the flattened fp32 partition. if not is_adagrad: self._optimizer_step(i) @@ -906,7 +906,7 @@ def initialize_optimizer_states(self): f'[End] Initialize optimizer states {i} / {num_subgroups} subgroups, num_elems: {num_elements}, swappable opt/param:{swappable_optimizer_subgroup}/{swappable_param_subgroup}', force=False) - # Initialize the optimizer states with the flattended fp32 partition. + # Initialize the optimizer states with the flattened fp32 partition. if is_adagrad: self.optimizer = torch.optim.Adagrad(self.fp32_partitioned_groups_flat, **self.optimizer.defaults) diff --git a/deepspeed/runtime/zero/stage_1_and_2.py b/deepspeed/runtime/zero/stage_1_and_2.py index 67fdcba65ea55..8f15b87af0e2a 100755 --- a/deepspeed/runtime/zero/stage_1_and_2.py +++ b/deepspeed/runtime/zero/stage_1_and_2.py @@ -611,7 +611,7 @@ def initialize_optimizer_states(self): self.single_partition_of_fp32_groups[i].grad = get_accelerator().pin_memory( single_grad_partition) if self.cpu_offload else single_grad_partition - # Initialize the optimizer states with the flattended fp32 partition. + # Initialize the optimizer states with the flattened fp32 partition. # State initialization for the Adagrad optimizer occurs at construction as opposed to other optimizers # which do lazy initialization of the state at the first call to step. if isinstance(self.optimizer, torch.optim.Adagrad): From 4559aa9b02bf9f113951e0092ebecc21debf8e20 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Bu=C4=9Fra?= <11869756+bgr8@users.noreply.github.com> Date: Fri, 2 Jun 2023 20:54:00 +0300 Subject: [PATCH 13/32] Refactor check_enabled root validator in DeepSpeedMonitorConfig (#3616) * Refactor check_enabled root validator in DeepSpeedMonitorConfig * formatting * formatting --------- Co-authored-by: Michael Wyatt Co-authored-by: Michael Wyatt --- deepspeed/monitor/config.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/deepspeed/monitor/config.py b/deepspeed/monitor/config.py index 0cd02603bd353..2706764290fdb 100644 --- a/deepspeed/monitor/config.py +++ b/deepspeed/monitor/config.py @@ -74,7 +74,6 @@ class DeepSpeedMonitorConfig(DeepSpeedConfigModel): @root_validator def check_enabled(cls, values): - values["enabled"] = False - if (values.get("tensorboard").enabled or values.get("wandb").enabled or values.get("csv_monitor").enabled): - values["enabled"] = True + values["enabled"] = values.get("tensorboard").enabled or values.get("wandb").enabled or values.get( + "csv_monitor").enabled return values From f483c0348bc141e40f2db44346d32f28da54ad4b Mon Sep 17 00:00:00 2001 From: Jeff Rasley Date: Fri, 2 Jun 2023 15:13:16 -0700 Subject: [PATCH 14/32] bump to 0.9.4 --- version.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/version.txt b/version.txt index 965065db5b84c..a602fc9e28338 100644 --- a/version.txt +++ b/version.txt @@ -1 +1 @@ -0.9.3 +0.9.4 From c88af2143248e4655d401f9231317f3c76018057 Mon Sep 17 00:00:00 2001 From: Zhen Zhang Date: Sun, 4 Jun 2023 17:26:46 -0700 Subject: [PATCH 15/32] [MiCS] [Fix] saving and loading model checkpoint logic for MiCS sharding (#3440) * fix mics save checkpoint hanging * MiCS load_checkpoint * copyright * fix for torch-1.9.0 all_reduce_coalesced api does not support nccl backend * Naming alignment * adding more test conditions for mics shard size * test with different shard sizes * adding assertion for better error msg --------- Co-authored-by: Zhen Zhang --- deepspeed/comm/torch.py | 13 +++- deepspeed/runtime/engine.py | 4 +- deepspeed/runtime/zero/mics.py | 18 +++-- tests/small_model_debugging/test_mics.sh | 9 +++ .../small_model_debugging/test_mics_config.py | 20 ++++-- tests/unit/checkpoint/test_mics_optimizer.py | 66 +++++++++++++++++++ 6 files changed, 115 insertions(+), 15 deletions(-) create mode 100755 tests/small_model_debugging/test_mics.sh create mode 100644 tests/unit/checkpoint/test_mics_optimizer.py diff --git a/deepspeed/comm/torch.py b/deepspeed/comm/torch.py index 2b8c8e4315eb1..208416c533aa1 100644 --- a/deepspeed/comm/torch.py +++ b/deepspeed/comm/torch.py @@ -20,13 +20,24 @@ def is_torch_two(): return False +def torch_ver_ge_1_13(): + if is_torch_two(): + return True + else: + TORCH_MAJOR = int(torch.__version__.split('.')[0]) + assert TORCH_MAJOR == 1 + + TORCH_MINOR = int(torch.__version__.split('.')[1]) + return TORCH_MINOR >= 13 + + def has_coalescing_manager(): has_c10d = hasattr(torch.distributed, 'distributed_c10d') return has_c10d and hasattr(torch.distributed.distributed_c10d, '_coalescing_manager') def has_all_reduce_coalesced(): - return hasattr(torch.distributed, "all_reduce_coalesced") + return hasattr(torch.distributed, "all_reduce_coalesced") and torch_ver_ge_1_13() def get_coalescing_manager(group, device, reqs): diff --git a/deepspeed/runtime/engine.py b/deepspeed/runtime/engine.py index 903da363ccf9d..f0fef9bcc4656 100644 --- a/deepspeed/runtime/engine.py +++ b/deepspeed/runtime/engine.py @@ -3057,11 +3057,11 @@ def _create_checkpoint_file(self, save_dir, tag, zero_checkpoint): def _create_zero_checkpoint_files(self, save_dir, tag): success = True # zero checkpoint files are created sequentially - for rank in range(self.world_size): + for rank in range(dist.get_world_size(self.optimizer.dp_process_group)): if rank == self.global_rank: success = self._create_checkpoint_file(save_dir, tag, True) - dist.barrier() + dist.barrier(group=self.optimizer.dp_process_group) return success diff --git a/deepspeed/runtime/zero/mics.py b/deepspeed/runtime/zero/mics.py index 09d2fedbc6064..b32e9e6fae1b7 100755 --- a/deepspeed/runtime/zero/mics.py +++ b/deepspeed/runtime/zero/mics.py @@ -393,15 +393,20 @@ def __init__(self, gradient_accumulation_steps, elastic_checkpoint, aio_config) first_param = next(module.parameters()) # overload the dp_process_group and partition_count + assert hasattr(first_param, "comm"), " ".join([ + "Sharded parameters don't have the MiCS_CommGroups attached.", + "Might due to the use of deepspeed.zero.Init context for initializing the weights.", + "To use MiCS sharding, please use deepspeed.zero.MiCS_Init instead for initializing parameter." + ]) self.dp_process_group = first_param.comm.param_shard_group self.partition_count = first_param.comm.param_shard_size def initialize_ds_offload(self, module, timers, ds_config, overlap_comm, prefetch_bucket_size, max_reuse_distance, max_live_parameters, param_persistence_threshold, model_persistence_threshold, - offload_optimizer_config, mpu): + offload_param_config, mpu): return MiCS_Offload(module, timers, ds_config, overlap_comm, prefetch_bucket_size, max_reuse_distance, max_live_parameters, param_persistence_threshold, model_persistence_threshold, - offload_optimizer_config, mpu) + offload_param_config, mpu) def partition_grads(self, params_to_release: List[Parameter], grad_partitions: List[Tensor]) -> None: grad_buffers = super().partition_grads(params_to_release, grad_partitions) @@ -440,14 +445,13 @@ def allreduce_mics_shard_grads(self, params, partitioned_grads_buffers: List[Ten grad_buff.view(-1).copy_(aggregated_buffer.narrow(0, offset, grad_buff.numel())) offset += grad_buff.numel() - # TODO: Support different/changing load/save DP degree. def load_state_dict(self, state_dict_list, load_optimizer_states=True, load_from_fp32_weights=False, checkpoint_folder=None): - r""" Loading the MiCS checkpoints - - TODO: move the implementation from zhen/merged_ds_master branch + r""" Loading the ZeRO-3/MiCS partitioned checkpoints + Because the self.dp_process_group is replaced with the communicator for + partition group we can call the load_state_dict logic from ZeRO-3. """ - raise NotImplementedError("Not implemented for loading MiCS checkpoints") + super().load_state_dict(state_dict_list, load_optimizer_states, load_from_fp32_weights, checkpoint_folder) diff --git a/tests/small_model_debugging/test_mics.sh b/tests/small_model_debugging/test_mics.sh new file mode 100755 index 0000000000000..9f306a7055d36 --- /dev/null +++ b/tests/small_model_debugging/test_mics.sh @@ -0,0 +1,9 @@ +#!/bin/bash + +deepspeed test_mics_config.py --mics_shard_size=1 + +deepspeed test_mics_config.py --mics_shard_size=2 + +# for debugging the hierarchical params gathering +export NDEV_PER_NODE=2 +deepspeed test_mics_config.py --mics_shard_size=4 --mics_hierarchical_params_gather diff --git a/tests/small_model_debugging/test_mics_config.py b/tests/small_model_debugging/test_mics_config.py index e988f9844e3b7..ccb34fadaefe3 100644 --- a/tests/small_model_debugging/test_mics_config.py +++ b/tests/small_model_debugging/test_mics_config.py @@ -5,6 +5,10 @@ # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 +""" +Testing on a 8 GPUs node +NDEV_PER_NODE=2 torchrun --nnodes 1 --nproc-per-node 8 test_mics_config.py +""" import os import json @@ -39,7 +43,7 @@ def create_config_from_dict(tmpdir, config_dict): def get_data_loader(model, total_samples, hidden_dim, device): batch_size = model.train_micro_batch_size_per_gpu() - train_data = torch.randn(total_samples, hidden_dim, device=device, dtype=torch.half) + train_data = torch.randn(total_samples, hidden_dim, device=device, dtype=torch.float) train_label = torch.empty(total_samples, dtype=torch.long, device=device).random_(hidden_dim) train_dataset = torch.utils.data.TensorDataset(train_data, train_label) sampler = DistributedSampler(train_dataset) @@ -49,11 +53,17 @@ def get_data_loader(model, total_samples, hidden_dim, device): def get_args(tmpdir, config_dict): parser = argparse.ArgumentParser() - parser.add_argument("--local_rank", type=int, default=0) parser.add_argument('--zero', type=int, default=3) + parser.add_argument('--local_rank', type=int) + + parser.add_argument('--mics_shard_size', default=2, type=int) + parser.add_argument('--mics_hierarchical_params_gather', default=False, action='store_true') args = parser.parse_args() #args='' config_dict["zero_optimization"]["stage"] = args.zero + config_dict["zero_optimization"]["mics_shard_size"] = args.mics_shard_size + config_dict["zero_optimization"]["mics_hierarchical_params_gather"] = args.mics_hierarchical_params_gather + # print('config_dict["zero_optimization"]', config_dict["zero_optimization"]) config_path = create_config_from_dict(tmpdir, config_dict) @@ -80,7 +90,7 @@ def print0(msg): } }, "fp16": { - "enabled": True, + "enabled": False, "initial_scale_power": 15 }, "zero_optimization": { @@ -95,8 +105,8 @@ def print0(msg): args = get_args('/tmp/', config_dict) hidden_dim = 32 -# with deepspeed.zero.Init(): -model = SimpleModel(hidden_dim, empty_grad=False) +with deepspeed.zero.MiCS_Init(config_dict_or_path=config_dict): + model = SimpleModel(hidden_dim, empty_grad=False) # print('------> init model with deepspeed.zero.Init()') model, _, _, _ = deepspeed.initialize(args=args, diff --git a/tests/unit/checkpoint/test_mics_optimizer.py b/tests/unit/checkpoint/test_mics_optimizer.py new file mode 100644 index 0000000000000..73d6e2fde48e7 --- /dev/null +++ b/tests/unit/checkpoint/test_mics_optimizer.py @@ -0,0 +1,66 @@ +# Copyright (c) Microsoft Corporation. +# SPDX-License-Identifier: Apache-2.0 + +# DeepSpeed Team + +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# SPDX-License-Identifier: Apache-2.0 + +import deepspeed + +from unit.common import DistributedTest +from unit.simple_model import * + +from unit.checkpoint.common import * + +import pytest + + +class TestMiCSCheckpoint(DistributedTest): + world_size = 4 + + def _toy_model_config(self, shard_size): + + config_dict = { + "train_micro_batch_size_per_gpu": 2, + "steps_per_print": 1, + "optimizer": { + "type": 'Adam', + "params": { + "lr": 0.00015, + "betas": [0.8, 0.999], + "eps": 1e-8, + "weight_decay": 3e-7 + } + }, + "fp16": { + "enabled": True, + "initial_scale_power": 8 + }, + "wall_clock_breakdown": True, + "zero_optimization": { + "stage": 3, + "mics_shard_size": shard_size + } + } + + hidden_dim = 10 + with deepspeed.zero.MiCS_Init(config_dict_or_path=config_dict): + models = [SimpleModel(hidden_dim, empty_grad=False) for _ in range(2)] + + return config_dict, hidden_dim, models + + @pytest.mark.parametrize('shard_size', [1, 2, 4]) + def test_load_optimizer_state(self, tmpdir, shard_size): + config_dict, hidden_dim, models = self._toy_model_config(shard_size) + checkpoint_correctness_verification(config_dict, models, hidden_dim, tmpdir, load_optimizer_states=True) + + @pytest.mark.parametrize('shard_size', [1, 2, 4]) + def test_not_load_optimizer_state(self, tmpdir, shard_size): + config_dict, hidden_dim, models = self._toy_model_config(shard_size) + checkpoint_correctness_verification(config_dict, models, hidden_dim, tmpdir, load_optimizer_states=False) + + @pytest.mark.parametrize('shard_size', [1, 2, 4]) + def test_load_module_only(self, tmpdir, shard_size): + config_dict, hidden_dim, models = self._toy_model_config(shard_size) + checkpoint_correctness_verification(config_dict, models, hidden_dim, tmpdir, load_module_only=True) From 3fb3cfdced941d8c7856c020812054141f8eab2c Mon Sep 17 00:00:00 2001 From: digger yu Date: Tue, 6 Jun 2023 06:22:52 +0800 Subject: [PATCH 16/32] fix some typo (#3675) * fix typo deepspeed/runtime * fix some typo --------- Co-authored-by: Olatunji Ruwase --- accelerator/real_accelerator.py | 6 +++--- blogs/deepspeed-chat/chinese/README.md | 2 +- deepspeed/autotuning/tuner/model_based_tuner.py | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/accelerator/real_accelerator.py b/accelerator/real_accelerator.py index 16705375b7104..b9bdc4ccf90d2 100644 --- a/accelerator/real_accelerator.py +++ b/accelerator/real_accelerator.py @@ -72,12 +72,12 @@ def get_accelerator(): accelerator_name = 'xpu' except ImportError as e: # We need a way to choose between CUDA_Accelerator and CPU_Accelerator - # Currently we detect whether intel_etension_for_pytorch is installed - # in the environment and use CPU_Accelerator if the answewr is True. + # Currently we detect whether intel_extension_for_pytorch is installed + # in the environment and use CPU_Accelerator if the answer is True. # An alternative might be detect whether CUDA device is installed on # the system but this comes with two pitfalls: # 1. the system may not have torch pre-installed, so - # get_accelerator().is_avaiable() may not work. + # get_accelerator().is_available() may not work. # 2. Some scenario like install on login node (without CUDA device) # and run on compute node (with CUDA device) may cause mismatch # between installation time and runtime. diff --git a/blogs/deepspeed-chat/chinese/README.md b/blogs/deepspeed-chat/chinese/README.md index c2e648ed3628b..f8e9de191d5fd 100644 --- a/blogs/deepspeed-chat/chinese/README.md +++ b/blogs/deepspeed-chat/chinese/README.md @@ -107,7 +107,7 @@ python train.py --actor-model facebook/opt-13b --reward-model facebook/opt-350m ``` Human: Do you know Microsoft? Assistant: Yes, I’m a big fan of Microsoft. What about them? -Human: Can you explian it to a 6-year old child? I wonder how I should describe it +Human: Can you explain it to a 6-year old child? I wonder how I should describe it Assistant: Sure, I can try. Microsoft is a company that makes computers, and they make a program called “Windows” which is the operating system that runs on the computer. It’s like the “brain” of the computer. It’s where all the programs and files are stored. It’s also where you’ll find the “start” button, which is where you’ll start to diff --git a/deepspeed/autotuning/tuner/model_based_tuner.py b/deepspeed/autotuning/tuner/model_based_tuner.py index 23f224b5eba20..aec9264f9b7c8 100755 --- a/deepspeed/autotuning/tuner/model_based_tuner.py +++ b/deepspeed/autotuning/tuner/model_based_tuner.py @@ -19,9 +19,9 @@ class ModelBasedTuner(BaseTuner): """Exploring the search space with a cost model""" - def __init__(self, exps: list, resource_manager, metric, tuning_sapce): + def __init__(self, exps: list, resource_manager, metric, tuning_space): super().__init__(exps, resource_manager, metric) - self.tuning_space = tuning_sapce + self.tuning_space = tuning_space self.best_iter = 0 self.all_configs = [e['ds_config'] for e in exps] From e5fe5f65e8be68364210f0173f1d1c4ab58a4ab7 Mon Sep 17 00:00:00 2001 From: Olatunji Ruwase Date: Mon, 5 Jun 2023 22:20:25 -0400 Subject: [PATCH 17/32] Use logger in accelerator (#3682) * Use logger in accelerator * Handle pre-build cases * Explain possible import failure --- accelerator/real_accelerator.py | 33 +++++++++++++++++++++------------ 1 file changed, 21 insertions(+), 12 deletions(-) diff --git a/accelerator/real_accelerator.py b/accelerator/real_accelerator.py index b9bdc4ccf90d2..de8f03889ddb5 100644 --- a/accelerator/real_accelerator.py +++ b/accelerator/real_accelerator.py @@ -4,6 +4,13 @@ # DeepSpeed Team import os +try: + # Importing logger currently requires that torch is installed, hence the try...except + # TODO: Remove logger dependency on torch. + from deepspeed.utils import logger as accel_logger +except ImportError as e: + accel_logger = None + try: from accelerator.abstract_accelerator import DeepSpeedAccelerator as dsa1 except ImportError as e: @@ -99,14 +106,16 @@ def get_accelerator(): # XPU_Accelerator is already imported in detection stage ds_accelerator = XPU_Accelerator() _validate_accelerator(ds_accelerator) - print(f"Setting ds_accelerator to {ds_accelerator._name} ({ds_set_method})") + if accel_logger is not None: + accel_logger.info(f"Setting ds_accelerator to {ds_accelerator._name} ({ds_set_method})") return ds_accelerator def set_accelerator(accel_obj): global ds_accelerator _validate_accelerator(accel_obj) - print(f"Setting ds_accelerator to {accel_obj._name} (model specified)") + if accel_logger is not None: + accel_logger.info(f"Setting ds_accelerator to {accel_obj._name} (model specified)") ds_accelerator = accel_obj @@ -114,10 +123,10 @@ def set_accelerator(accel_obj): -----------[code] test_get.py ----------- from deepspeed.accelerator import get_accelerator my_accelerator = get_accelerator() -print(f'{my_accelerator._name=}') -print(f'{my_accelerator._communication_backend=}') -print(f'{my_accelerator.HalfTensor().device=}') -print(f'{my_accelerator.total_memory()=}') +logger.info(f'{my_accelerator._name=}') +logger.info(f'{my_accelerator._communication_backend=}') +logger.info(f'{my_accelerator.HalfTensor().device=}') +logger.info(f'{my_accelerator.total_memory()=}') -----------[code] test_get.py ----------- ---[output] python test_get.py--------- @@ -131,16 +140,16 @@ def set_accelerator(accel_obj): -----------[code] test_set.py ----------- from deepspeed.accelerator.cuda_accelerator import CUDA_Accelerator cu_accel = CUDA_Accelerator() -print(f'{id(cu_accel)=}') +logger.info(f'{id(cu_accel)=}') from deepspeed.accelerator import set_accelerator, get_accelerator set_accelerator(cu_accel) my_accelerator = get_accelerator() -print(f'{id(my_accelerator)=}') -print(f'{my_accelerator._name=}') -print(f'{my_accelerator._communication_backend=}') -print(f'{my_accelerator.HalfTensor().device=}') -print(f'{my_accelerator.total_memory()=}') +logger.info(f'{id(my_accelerator)=}') +logger.info(f'{my_accelerator._name=}') +logger.info(f'{my_accelerator._communication_backend=}') +logger.info(f'{my_accelerator.HalfTensor().device=}') +logger.info(f'{my_accelerator.total_memory()=}') -----------[code] test_set.py ----------- From 2d737eddcc44c838a8bc7f934d7dd9cc31bd2b9c Mon Sep 17 00:00:00 2001 From: Siddharth Singh Date: Tue, 6 Jun 2023 06:48:49 -0700 Subject: [PATCH 18/32] Update README to add ICS'23 paper (#3687) --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index e801daba4dbf6..66a62ffd6b6fe 100755 --- a/README.md +++ b/README.md @@ -223,6 +223,7 @@ Conduct](https://opensource.microsoft.com/codeofconduct/). For more information 18. Syed Zawad, Cheng Li, Zhewei Yao, Elton Zheng, Yuxiong He, Feng Yan. (2023) DySR: Adaptive Super-Resolution via Algorithm and System Co-design. [ICLR:2023](https://openreview.net/forum?id=Pgtn4l6eKjv). 19. Sheng Shen, Zhewei Yao, Chunyuan Li, Trevor Darrell, Kurt Keutzer, Yuxiong He. (2023) Scaling Vision-Language Models with Sparse Mixture of Experts. [arXiv:2303.07226](https://arxiv.org/abs/2303.07226). 20. Quentin Anthony, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He, Aamir Shafi, Mustafa Abduljabbar, Hari Subramoni, Dhabaleswar Panda. (2023) MCR-DL: Mix-and-Match Communication Runtime for Deep Learning [arXiv:2303.08374](https://arxiv.org/abs/2303.08374) and will appear at IPDPS 2023. +21. Siddharth Singh, Olatunji Ruwase, Ammar Ahmad Awan, Samyam Rajbhandari, Yuxiong He, Abhinav Bhatele. (2023) A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training [arXiv:2303.06318](https://arxiv.org/abs/2303.06318) and will appear at ICS 2023. # Videos From 4cd0a003f5b6744a3455c34ad0d20364a8627b30 Mon Sep 17 00:00:00 2001 From: Ramya Ramineni <62723901+rraminen@users.noreply.github.com> Date: Tue, 6 Jun 2023 11:25:12 -0500 Subject: [PATCH 19/32] non-JIT build fix on ROCm (#3638) Co-authored-by: Olatunji Ruwase Co-authored-by: Michael Wyatt Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com> --- op_builder/builder.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/op_builder/builder.py b/op_builder/builder.py index e2902918f580e..03b5b2fca756c 100644 --- a/op_builder/builder.py +++ b/op_builder/builder.py @@ -601,7 +601,8 @@ def is_compatible(self, verbose=True): def builder(self): try: - assert_no_cuda_mismatch(self.name) + if not self.is_rocm_pytorch(): + assert_no_cuda_mismatch(self.name) self.build_for_cpu = False except BaseException: self.build_for_cpu = True From b7f463ddeb00f8a4119520383759b201bc572b07 Mon Sep 17 00:00:00 2001 From: Byungsoo Oh Date: Wed, 7 Jun 2023 07:14:07 +0900 Subject: [PATCH 20/32] Fix local rank mismatch for heterogeneous nodes (#3409) Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com> Co-authored-by: Olatunji Ruwase --- deepspeed/launcher/launch.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/deepspeed/launcher/launch.py b/deepspeed/launcher/launch.py index 295515fcecc6f..b3cb9d1205a91 100755 --- a/deepspeed/launcher/launch.py +++ b/deepspeed/launcher/launch.py @@ -215,9 +215,10 @@ def main(): raise ValueError(f"unable to create directory {args.enable_each_rank_log} for each rank log.") log_name_prefix = time.strftime("%Y%m%d%H%M%S", time.localtime()) - for local_rank in range(0, num_local_procs): + for local_proc in range(0, num_local_procs): # each process's rank - dist_rank = global_rank_mapping[local_node][local_rank] + dist_rank = global_rank_mapping[local_node][local_proc] + local_rank = dist_rank % num_local_procs current_env["RANK"] = str(dist_rank) current_env["LOCAL_RANK"] = str(local_rank) From c17313fb241ddf4ccc8c2b8b135cbcc5e9e89ce5 Mon Sep 17 00:00:00 2001 From: Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com> Date: Wed, 7 Jun 2023 05:06:25 +0530 Subject: [PATCH 21/32] Correct world_size/backend for mpi (#3694) Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com> --- deepspeed/comm/backend.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/deepspeed/comm/backend.py b/deepspeed/comm/backend.py index 4e02ad89719c0..15dc96c405212 100644 --- a/deepspeed/comm/backend.py +++ b/deepspeed/comm/backend.py @@ -28,8 +28,8 @@ def __init__(self, name='backend', rank=0, size=1): self.name = name # The world size and rank of the world process group self.world_group = None - self.world_size = rank - self.world_rank = size + self.world_size = size + self.world_rank = rank # Single process group (pg) implementation for now but keep a list for future self.process_groups = [] self.initialized = False From d8aaa581223f00f84645629d4c0e31879827937f Mon Sep 17 00:00:00 2001 From: Logan Adams <114770087+loadams@users.noreply.github.com> Date: Tue, 6 Jun 2023 16:42:14 -0700 Subject: [PATCH 22/32] Fix incorrectly formatted f string (#3698) Co-authored-by: Michael Wyatt --- deepspeed/launcher/runner.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepspeed/launcher/runner.py b/deepspeed/launcher/runner.py index c397cf48fbe2c..a8191f25cec5c 100755 --- a/deepspeed/launcher/runner.py +++ b/deepspeed/launcher/runner.py @@ -227,7 +227,7 @@ def _parse_hostfile(hostfile_lines): resource_pool[host] = num_slots else: logger.error(f"Bad hostfile text: {hostfile_lines}") - raise ValueError("Hostfile contains a bad entry: {line}, unable to proceed with launching") + raise ValueError(f"Hostfile contains a bad entry: {line}, unable to proceed with launching") if len(resource_pool) == 0: logger.error(f"Bad hostfile text: {hostfile_lines}") From f2f5f21b52a82de75c85abd190ecd328ce762c5a Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Wed, 7 Jun 2023 07:43:29 +0800 Subject: [PATCH 23/32] fix typo name (#3689) Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com> Co-authored-by: Michael Wyatt --- deepspeed/module_inject/containers/features/split_qkv.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepspeed/module_inject/containers/features/split_qkv.py b/deepspeed/module_inject/containers/features/split_qkv.py index aff4877835f80..f91fe815f92af 100644 --- a/deepspeed/module_inject/containers/features/split_qkv.py +++ b/deepspeed/module_inject/containers/features/split_qkv.py @@ -123,7 +123,7 @@ def reset_qkv_experimental(self): for data in qkv_data: del data - def set_attn_parameters_wo_copy(self, Z3_enabled=False): + def set_attn_params_wo_copy(self, Z3_enabled=False): self.module.attention.attn_ow = self.dense_w self.module.attention.attn_ob = self.dense_b if not Z3_enabled: From 7e59ef12300032fc50683fae534cbd41ec1475b0 Mon Sep 17 00:00:00 2001 From: Logan Adams <114770087+loadams@users.noreply.github.com> Date: Wed, 7 Jun 2023 09:56:21 -0700 Subject: [PATCH 24/32] Revert "fix typo name (#3689)" (#3702) This reverts commit f2f5f21b52a82de75c85abd190ecd328ce762c5a. --- deepspeed/module_inject/containers/features/split_qkv.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepspeed/module_inject/containers/features/split_qkv.py b/deepspeed/module_inject/containers/features/split_qkv.py index f91fe815f92af..aff4877835f80 100644 --- a/deepspeed/module_inject/containers/features/split_qkv.py +++ b/deepspeed/module_inject/containers/features/split_qkv.py @@ -123,7 +123,7 @@ def reset_qkv_experimental(self): for data in qkv_data: del data - def set_attn_params_wo_copy(self, Z3_enabled=False): + def set_attn_parameters_wo_copy(self, Z3_enabled=False): self.module.attention.attn_ow = self.dense_w self.module.attention.attn_ob = self.dense_b if not Z3_enabled: From 34a9fbf1a3f1c5b992bcea92b1b1aa8ba9ea5cc0 Mon Sep 17 00:00:00 2001 From: Reza Yazdani <44502768+RezaYazdaniAminabadi@users.noreply.github.com> Date: Wed, 7 Jun 2023 12:38:46 -0700 Subject: [PATCH 25/32] Fix gpt-j inference issue (#3639) * fix gpt-j inference issue for mlp_gemm_func call * bring back the gpt-j inference-test * fix formatting * fix the neox and pythia injection issue --- deepspeed/module_inject/containers/base.py | 24 +++++++++++++--------- tests/unit/inference/test_inference.py | 2 +- 2 files changed, 15 insertions(+), 11 deletions(-) diff --git a/deepspeed/module_inject/containers/base.py b/deepspeed/module_inject/containers/base.py index a0dc3e98de355..a520664793ca6 100644 --- a/deepspeed/module_inject/containers/base.py +++ b/deepspeed/module_inject/containers/base.py @@ -249,17 +249,21 @@ def mlp_output_mp(self, mp_replace, reversed_dim=False): allocate_tensor=reversed_dim) def copy_data_to_new_module(self): - params = { - self.module.mlp.attn_nw: self.attn_nw, - self.module.mlp.attn_nb: self.attn_nb, - self.module.norm_w: self.input_nw, - self.module.norm_b: self.input_nb - } - for dst, src in params.items(): - if src is None: - dst = src + params = {'attn_nw': self.attn_nw, 'attn_nb': self.attn_nb} + for key in params: + if params[key] is None: + setattr(self.module.mlp, key, None) else: - dst.data.copy_(src.to(get_accelerator().current_device_name())) + setattr(self.module.mlp, key, + torch.nn.parameter.Parameter(params[key].to(get_accelerator().current_device_name()))) + + params = {'norm_w': self.input_nw, 'norm_b': self.input_nb} + for key in params: + if params[key] is None: + setattr(self.module, key, None) + else: + setattr(self.module, key, + torch.nn.parameter.Parameter(params[key].to(get_accelerator().current_device_name()))) def transpose(self): self.transpose_attention() diff --git a/tests/unit/inference/test_inference.py b/tests/unit/inference/test_inference.py index 65365837a0b87..c42deb3dd6d74 100644 --- a/tests/unit/inference/test_inference.py +++ b/tests/unit/inference/test_inference.py @@ -49,7 +49,7 @@ "gpt2", "distilgpt2", "Norod78/hebrew-bad_wiki-gpt_neo-tiny", - #"EleutherAI/gpt-j-6B", # Removed as this is causing OOM errors randomly + "EleutherAI/gpt-j-6B", # bring back this model as we did not catch an error before by merging some changes! TODO: we need to fix the OOM issue later! "bigscience/bloom-560m", ] _opt_models = [ From c5edc91ecb5a080d8110f2b4dfbc323f8f767116 Mon Sep 17 00:00:00 2001 From: digger yu Date: Thu, 8 Jun 2023 06:33:43 +0800 Subject: [PATCH 26/32] change partititon_name to partition_name (#3700) Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com> --- .../checkpoint_engine/nebula_checkpoint_engine.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/deepspeed/runtime/checkpoint_engine/nebula_checkpoint_engine.py b/deepspeed/runtime/checkpoint_engine/nebula_checkpoint_engine.py index 147f2d30695fc..e26e3243c4b5d 100644 --- a/deepspeed/runtime/checkpoint_engine/nebula_checkpoint_engine.py +++ b/deepspeed/runtime/checkpoint_engine/nebula_checkpoint_engine.py @@ -46,10 +46,10 @@ def save(self, state_dict, path: str): torch.save("", path) tag = _get_tag_from_path(path) - partititon_name = os.path.basename(path) - logger.info(f"[Nebula] Saving {partititon_name} under tag {tag}...") - self.checkpoint.save(partititon_name, state_dict) - logger.info(f"[Nebula] Saved {partititon_name} under tag {tag}.") + partition_name = os.path.basename(path) + logger.info(f"[Nebula] Saving {partition_name} under tag {tag}...") + self.checkpoint.save(partition_name, state_dict) + logger.info(f"[Nebula] Saved {partition_name} under tag {tag}.") return None def load(self, path: str, map_location=None): @@ -62,7 +62,7 @@ def load(self, path: str, map_location=None): logger.info(f"[Nebula] Disable nebula load. Loaded checkpoint from {path} .") return partition - partititon_name = os.path.basename(path) + partition_name = os.path.basename(path) logger.info(f"[Nebula] Loading {path} under tag {tag} from nebula path {self.nebula_load_path}...") checkpoint = None @@ -93,7 +93,7 @@ def load(self, path: str, map_location=None): tag = checkpoint.tag self.tag_flag = -1 - partition = checkpoint.load(partititon_name, map_location=map_location) + partition = checkpoint.load(partition_name, map_location=map_location) logger.info(f"[Nebula] Loaded {path} under tag {tag} from {self.nebula_load_path}.") return partition From fb2b4ab11a5a2bbeb998b82aba1205d2bdd06152 Mon Sep 17 00:00:00 2001 From: Michael Wyatt Date: Wed, 7 Jun 2023 16:53:37 -0700 Subject: [PATCH 27/32] Fix unit test typo in tests/unit/ops/transformer/inference (#3697) * mix typo and missing epsilon value * Touch file to re-build * revert changes * Touch file to re-build * Format --------- Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com> Co-authored-by: Logan Adams --- .../unit/ops/transformer/inference/test_layer_norm.py | 10 +++++++--- tests/unit/ops/transformer/inference/test_rms_norm.py | 4 ++-- 2 files changed, 9 insertions(+), 5 deletions(-) diff --git a/tests/unit/ops/transformer/inference/test_layer_norm.py b/tests/unit/ops/transformer/inference/test_layer_norm.py index f44b977ac45d6..25728d41a0cd8 100644 --- a/tests/unit/ops/transformer/inference/test_layer_norm.py +++ b/tests/unit/ops/transformer/inference/test_layer_norm.py @@ -55,7 +55,10 @@ def residual_ref_implementation(vals, bias, res, gamma, beta, epsilon, channels, res_f = res.to(torch.float32) gamma_f = gamma.to(torch.float32) beta_f = beta.to(torch.float32) - return torch.nn.functional.layer_norm(vals_f + bias_f + res_f, (channels, ), weight=gamma_f, bias=beta_f).to(dtype) + return torch.nn.functional.layer_norm(vals_f + bias_f + res_f, (channels, ), + weight=gamma_f, + bias=beta_f, + eps=epsilon).to(dtype) def residual_ds_implementation(vals, bias, res, gamma, beta, epsilon): @@ -86,14 +89,15 @@ def test_layer_norm_residual(batch, seq_len, channels, dtype): assert allclose(new_output, ref_output) -def residual_store_ref_implementation(vals, bias, res, gamma, beta, espilon, channels, dtype): +def residual_store_ref_implementation(vals, bias, res, gamma, beta, epsilon, channels, dtype): vals_f = vals.to(torch.float32) bias_f = bias.to(torch.float32).reshape(1, 1, -1) res_f = res.to(torch.float32) gamma_f = gamma.to(torch.float32) beta_f = beta.to(torch.float32) res_output = vals_f + bias_f + res_f - norm_output = torch.nn.functional.layer_norm(res_output, (channels, ), weight=gamma_f, bias=beta_f).to(dtype) + norm_output = torch.nn.functional.layer_norm(res_output, (channels, ), weight=gamma_f, bias=beta_f, + eps=epsilon).to(dtype) return norm_output, res_output.to(dtype) diff --git a/tests/unit/ops/transformer/inference/test_rms_norm.py b/tests/unit/ops/transformer/inference/test_rms_norm.py index 1ae8f060673af..508a40e12e8df 100644 --- a/tests/unit/ops/transformer/inference/test_rms_norm.py +++ b/tests/unit/ops/transformer/inference/test_rms_norm.py @@ -16,9 +16,9 @@ inference_module = None -def ref_implementation(vals, gamma, espilon): +def ref_implementation(vals, gamma, epsilon): variance = vals.to(torch.float32).pow(2).mean(-1, keepdim=True) - vals = vals * torch.rsqrt(variance + espilon) + vals = vals * torch.rsqrt(variance + epsilon) if gamma.dtype in [torch.float16, torch.bfloat16]: vals = vals.to(gamma.dtype) From d414678df77c8a6fb4bc112fb0aa3bd81d677d3f Mon Sep 17 00:00:00 2001 From: john li Date: Wed, 7 Jun 2023 19:59:35 -0400 Subject: [PATCH 28/32] Small tweak on cuda version mismatch documentation (#3706) * Small tweak on cuda version mismatch documentation * clarify minor versions should also match --------- Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com> --- docs/_tutorials/advanced-install.md | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) diff --git a/docs/_tutorials/advanced-install.md b/docs/_tutorials/advanced-install.md index c1153742f9642..31987e6a87db9 100755 --- a/docs/_tutorials/advanced-install.md +++ b/docs/_tutorials/advanced-install.md @@ -155,15 +155,20 @@ If you're getting the following error: Exception: >- DeepSpeed Op Builder: Installed CUDA version {VERSION} does not match the version torch was compiled with {VERSION}, unable to compile cuda/cpp extensions without a matching cuda version. ``` You have a misaligned version of CUDA installed compared to the version of CUDA -used to compile torch. We only require that major version match (e.g., 11.1 and -11.8 are OK). However a mismatch in the major version may result in unexpected -behavior and errors. +used to compile torch. A mismatch in the major version is likely to result in +errors or unexpected behavior. The easiest fix for this error is changing the CUDA version installed (check with `nvcc --version`) or updating the torch version to match the installed CUDA version (check with `python3 -c "import torch; print(torch.__version__)"`). -If you want to skip this check and proceed with the mismatched CUDA versions, use the following environment variable: +We only require that the major version matches (e.g., 11.1 and 11.8). However, +note that even a mismatch in the minor version _may still_ result in unexpected +behavior and errors, so it's recommended to match both major and minor versions. +When there's a minor version mismatch, DeepSpeed will log a warning. + +If you want to skip this check and proceed with the mismatched CUDA versions, +use the following environment variable, but beware of unexpected behavior: ```bash DS_SKIP_CUDA_CHECK=1 From df425097869214c3371d74a4cbd7c506bea3cef7 Mon Sep 17 00:00:00 2001 From: Conglong Li Date: Wed, 7 Jun 2023 20:20:46 -0700 Subject: [PATCH 29/32] DeepSpeed overview in Japanese (#3709) * DeepSpeed overview in Japanese * DeepSpeed overview in Japanese --- .../2023-06-07-deepspeed-overview-japanese.md | 8 ++++++++ ...DeepSpeed_Overview_Japanese_2023Jun7th.pdf | Bin 0 -> 3728948 bytes 2 files changed, 8 insertions(+) create mode 100644 docs/_posts/2023-06-07-deepspeed-overview-japanese.md create mode 100644 docs/assets/files/DeepSpeed_Overview_Japanese_2023Jun7th.pdf diff --git a/docs/_posts/2023-06-07-deepspeed-overview-japanese.md b/docs/_posts/2023-06-07-deepspeed-overview-japanese.md new file mode 100644 index 0000000000000..8f42093991c8d --- /dev/null +++ b/docs/_posts/2023-06-07-deepspeed-overview-japanese.md @@ -0,0 +1,8 @@ +--- +title: "DeepSpeed主要技術の概要紹介" +excerpt: "" +date: 2023-06-07 00:00:00 +tags: inference training ZeRO RLHF Japanese presentations +--- + +我々が研究開発しているDeepSpeedについて、主要技術を日本語で説明した資料を公開しました。GPT3やChatGPTのような生成型AIのための大規模言語モデルを含む、様々な深層学習の訓練や推論に容易に適用でき、モデルの大規模化、高速化、コスト削減を可能にします。[こちら](/assets/files/DeepSpeed_Overview_Japanese_2023Jun7th.pdf)よりダウンロードしてください。 diff --git a/docs/assets/files/DeepSpeed_Overview_Japanese_2023Jun7th.pdf b/docs/assets/files/DeepSpeed_Overview_Japanese_2023Jun7th.pdf new file mode 100644 index 0000000000000000000000000000000000000000..f65e9754700655ef95bd45d0b2e304e6c039a67c GIT binary patch literal 3728948 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