Drop torch 1.10, 1.11, 1.12

.flexci/config.pbtxt

@@ -1,51 +1,3 @@
-configs {
-  key: "pytorch-pfn-extras.torch110-linux"
-  value {
-    requirement {
-      cpu: 8
-      gpu: 2
-      memory: 52
-      disk: 10
-    }
-    time_limit: {
-      seconds: 1800
-    }
-    command: "bash .flexci/linux/main-flexci.sh torch110"
-  }
-}
-
-configs {
-  key: "pytorch-pfn-extras.torch111-linux"
-  value {
-    requirement {
-      cpu: 8
-      gpu: 2
-      memory: 52
-      disk: 10
-    }
-    time_limit: {
-      seconds: 1800
-    }
-    command: "bash .flexci/linux/main-flexci.sh torch111"
-  }
-}
-
-configs {
-  key: "pytorch-pfn-extras.torch112-linux"
-  value {
-    requirement {
-      cpu: 8
-      gpu: 2
-      memory: 52
-      disk: 10
-    }
-    time_limit: {
-      seconds: 1800
-    }
-    command: "bash .flexci/linux/main-flexci.sh torch112"
-  }
-}
-
 configs {
   key: "pytorch-pfn-extras.torch113-linux"
   value {
@@ -110,57 +62,6 @@ configs {
   }
 }
 
-configs {
-  key: "pytorch-pfn-extras.torch110-win"
-  value {
-    requirement {
-      cpu: 4
-      gpu: 1
-      memory: 24
-      disk: 10
-      image: "windows"
-    }
-    time_limit: {
-      seconds: 1800
-    }
-    command: ".flexci\\windows\\run.bat torch110"
-  }
-}
-
-configs {
-  key: "pytorch-pfn-extras.torch111-win"
-  value {
-    requirement {
-      cpu: 4
-      gpu: 1
-      memory: 24
-      disk: 10
-      image: "windows"
-    }
-    time_limit: {
-      seconds: 1800
-    }
-    command: ".flexci\\windows\\run.bat torch111"
-  }
-}
-
-configs {
-  key: "pytorch-pfn-extras.torch112-win"
-  value {
-    requirement {
-      cpu: 4
-      gpu: 1
-      memory: 24
-      disk: 10
-      image: "windows"
-    }
-    time_limit: {
-      seconds: 1800
-    }
-    command: ".flexci\\windows\\run.bat torch112"
-  }
-}
-
 configs {
   key: "pytorch-pfn-extras.torch113-win"
   value {

.flexci/linux/build_and_push.sh

@@ -27,33 +27,6 @@ docker_build_and_push() {
 }
 
 case "${TARGET}" in
-    torch110 )
-        # PyTorch 1.10 + Python 3.9
-        docker_build_and_push \
-            --build-arg base_image="nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04" \
-            --build-arg python_version="3.9.7" \
-            --build-arg pip_install_torch_args="torch==1.10.* torchvision==0.11.* -f https://download.pytorch.org/whl/cu113/torch_stable.html" \
-            --build-arg pip_install_dep_args="cupy-cuda11x"
-        ;;
-
-    torch111 )
-        # PyTorch 1.11 + Python 3.9
-        docker_build_and_push \
-            --build-arg base_image="nvidia/cuda:11.5.2-cudnn8-devel-ubuntu20.04" \
-            --build-arg python_version="3.9.7" \
-            --build-arg pip_install_torch_args="torch==1.11.* torchvision==0.12.* -f https://download.pytorch.org/whl/cu115/torch_stable.html" \
-            --build-arg pip_install_dep_args="cupy-cuda11x"
-        ;;
-
-    torch112 )
-        # PyTorch 1.12 + Python 3.10
-        docker_build_and_push \
-            --build-arg base_image="nvidia/cuda:11.7.1-cudnn8-devel-ubuntu20.04" \
-            --build-arg python_version="3.10.5" \
-            --build-arg pip_install_torch_args="torch==1.12.* torchvision==0.13.* -f https://download.pytorch.org/whl/cu117/torch_stable.html" \
-            --build-arg pip_install_dep_args="cupy-cuda11x"
-        ;;
-
     torch113 )
         # PyTorch 1.13 + Python 3.10
         docker_build_and_push \

.flexci/windows/test.ps1

@@ -9,40 +9,7 @@ $ErrorActionPreference = "Stop"
 
 
 # Setup environment
-if ($test -eq "torch110") {
-    # PyTorch 1.10 + Python 3.9
-    ActivateCUDA 11.8
-    ActivatePython 3.9
-    RunOrDie python -m pip install -U pip "setuptools<59.6"
-    RunOrDieWithRetry 3 python -m pip install torch==1.10.* torchvision==0.11.* -f https://download.pytorch.org/whl/cu113/torch_stable.html
-    # NOTE(linsho):
-    # Due to reports of the ONNX build for Windows being broken, we are temporarily limiting the version of ONNX.
-    # cf. https://github.com/onnx/onnx/issues/6267
-    RunOrDie python -m pip install -r tests/requirements.txt cupy-cuda11x "onnx<=1.16.1"
-
-} elseif ($test -eq "torch111") {
-    # PyTorch 1.11 + Python 3.9
-    ActivateCUDA 11.3
-    ActivatePython 3.9
-    RunOrDie python -m pip install -U pip "setuptools<59.6"
-    RunOrDieWithRetry 3 python -m pip install torch==1.11.* torchvision==0.12.* -f https://download.pytorch.org/whl/cu113/torch_stable.html
-    # NOTE(linsho):
-    # Due to reports of the ONNX build for Windows being broken, we are temporarily limiting the version of ONNX.
-    # cf. https://github.com/onnx/onnx/issues/6267
-    RunOrDie python -m pip install -r tests/requirements.txt cupy-cuda11x "onnx<=1.16.1"
-
-} elseif ($test -eq "torch112") {
-    # PyTorch 1.12 + Python 3.10
-    ActivateCUDA 11.3
-    ActivatePython 3.10
-    RunOrDie python -m pip install -U pip "setuptools<59.6"
-    RunOrDieWithRetry 3 python -m pip install torch==1.12.* torchvision==0.13.* -f https://download.pytorch.org/whl/cu113/torch_stable.html
-    # NOTE(linsho):
-    # Due to reports of the ONNX build for Windows being broken, we are temporarily limiting the version of ONNX.
-    # cf. https://github.com/onnx/onnx/issues/6267
-    RunOrDie python -m pip install -r tests/requirements.txt cupy-cuda11x "onnx<=1.16.1"
-
-} elseif ($test -eq "torch113") {
+if ($test -eq "torch113") {
     # PyTorch 1.13 + Python 3.10
     ActivateCUDA 11.7
     ActivatePython 3.10

.github/workflows/pretest-and-test.yml

@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-22.04
     strategy:
       matrix:
-        torch: ['1.10.*', '1.11.*', '1.12.*', '1.13.*', '2.0.*', '2.1.*', '2.2.*']
+        torch: ['1.13.*', '2.0.*', '2.1.*', '2.2.*']
 
     steps:
     - name: Checkout

README.md

@@ -28,7 +28,7 @@ pip install cupy  # or cupy-cudaXXX
 ## Requirements
 
 * Python 3.9+
-* PyTorch 1.10+
+* PyTorch 1.13+
 
 Optional dependencies:
 

pytorch_pfn_extras/onnx/_constants.py

@@ -2,15 +2,7 @@
 import torch.onnx
 import torch.onnx.symbolic_helper
 
-if pytorch_pfn_extras.requires("1.13.0"):
-    from torch.onnx._constants import ONNX_DEFAULT_OPSET, ONNX_CONSTANT_FOLDING_MIN_OPSET, ONNX_MAX_OPSET  # type: ignore[attr-defined]
-    onnx_default_opset = ONNX_DEFAULT_OPSET
-    onnx_constant_folding_opsets = range(ONNX_CONSTANT_FOLDING_MIN_OPSET, ONNX_MAX_OPSET)
-    onnx_main_opset = ONNX_MAX_OPSET
-elif pytorch_pfn_extras.requires("1.12.0"):
-    from torch.onnx._constants import *  # type: ignore # NOQA
-else:
-    onnx_default_opset = torch.onnx.symbolic_helper._default_onnx_opset_version  # type: ignore
-    onnx_main_opset = torch.onnx.symbolic_helper._onnx_main_opset  # type: ignore
-    onnx_stable_opsets = torch.onnx.symbolic_helper._onnx_stable_opsets  # type: ignore
-    onnx_constant_folding_opsets = torch.onnx.symbolic_helper._constant_folding_opset_versions if pytorch_pfn_extras.requires("1.11.0") else torch.onnx.constant_folding_opset_versions  # type: ignore[attr-defined]
+from torch.onnx._constants import ONNX_DEFAULT_OPSET, ONNX_CONSTANT_FOLDING_MIN_OPSET, ONNX_MAX_OPSET  # type: ignore[attr-defined]
+onnx_default_opset = ONNX_DEFAULT_OPSET
+onnx_constant_folding_opsets = range(ONNX_CONSTANT_FOLDING_MIN_OPSET, ONNX_MAX_OPSET)
+onnx_main_opset = ONNX_MAX_OPSET

pytorch_pfn_extras/onnx/_globals.py

@@ -3,28 +3,6 @@
 from typing import Optional
 
 
-if pytorch_pfn_extras.requires("1.12.0"):
-    import torch.onnx._globals
-    GLOBALS = torch.onnx._globals.GLOBALS
+import torch.onnx._globals
+GLOBALS = torch.onnx._globals.GLOBALS
 
-else:
-    import torch.onnx.symbolic_helper as symhel
-
-    class _InternalGlobalsBeforeTorch1_11:
-        @property
-        def export_onnx_opset_version(self) -> int:
-            return symhel._export_onnx_opset_version  # type: ignore
-
-        @property
-        def operator_export_type(self) -> Optional[torch._C._onnx.OperatorExportTypes]:
-            return symhel._operator_export_type  # type: ignore
-
-        @property
-        def training_mode(self) -> Optional[torch._C._onnx.TrainingMode]:
-            return symhel._training_mode  # type: ignore
-
-        @property
-        def onnx_shape_inference(self) -> bool:
-            return symhel._onnx_shape_inference  # type: ignore
-
-    GLOBALS = _InternalGlobalsBeforeTorch1_11()  # type: ignore[assignment]

pytorch_pfn_extras/onnx/annotate.py

@@ -31,10 +31,6 @@ def __init__(self) -> None:
     def setup(self, model: nn.Module, opset_ver: int) -> None:
         self._model: Optional[nn.Module] = model
         # dryrun to register every aten ops
-        if not pytorch_pfn_extras.requires("1.13.0"):
-            import pytorch_pfn_extras.onnx.symbolic_registry as sym_reg
-
-            sym_reg.register_version('', opset_ver)  # type: ignore[no-untyped-call,attr-defined]
         self.opset_ver = opset_ver
 
     @property

pytorch_pfn_extras/onnx/export_testcase.py

@@ -109,15 +109,9 @@ def _export_util(
     if aten or export_raw_ir:
         assert operator_export_type is None
         assert aten ^ export_raw_ir
-        # Note: OperatorExportTypes.RAW unavailable in PyTorch 1.10+
-        operator_export_type = OperatorExportTypes.ONNX_ATEN if\
-            aten else OperatorExportTypes.RAW  # type: ignore
+        operator_export_type = OperatorExportTypes.ONNX_ATEN
     elif operator_export_type is None:
-        if pytorch_pfn_extras.requires("1.12.0"):
-            use_onnx_aten_fallback = torch.onnx._CAFFE2_ATEN_FALLBACK  # type: ignore[attr-defined]
-        else:
-            use_onnx_aten_fallback = torch.onnx.PYTORCH_ONNX_CAFFE2_BUNDLE  # type: ignore[attr-defined]
-
+        use_onnx_aten_fallback = torch.onnx._CAFFE2_ATEN_FALLBACK  # type: ignore[attr-defined]
         if use_onnx_aten_fallback:
             operator_export_type = OperatorExportTypes.ONNX_ATEN_FALLBACK
         else:
@@ -128,24 +122,19 @@ def _export_util(
     # This is a temporal workaround until a fix is introduced in PyTorch.
     try:
         torch.onnx.utils._model_to_graph = _model_to_graph_with_value_names
-        if pytorch_pfn_extras.requires('1.10.0'):
-            checker_error = getattr(torch.onnx, "CheckerError", None)
-            if checker_error is None:
-                checker_error = torch.onnx.utils.ONNXCheckerError  # type: ignore[attr-defined]
-            try:
-                enable_onnx_checker = kwargs.pop('enable_onnx_checker', None)
-                return torch_export(  # type: ignore[no-untyped-call]
-                    model, args, f, **kwargs)
-            except checker_error:
-                if enable_onnx_checker:
-                    raise
-                if return_output:
-                    # Re-run the model to obtain the output.
-                    return model(*args)
-        else:
-            kwargs['_retain_param_name'] = True
+        checker_error = getattr(torch.onnx, "CheckerError", None)
+        if checker_error is None:
+            checker_error = torch.onnx.utils.ONNXCheckerError  # type: ignore[attr-defined]
+        try:
+            enable_onnx_checker = kwargs.pop('enable_onnx_checker', None)
             return torch_export(  # type: ignore[no-untyped-call]
                 model, args, f, **kwargs)
+        except checker_error:
+            if enable_onnx_checker:
+                raise
+            if return_output:
+                # Re-run the model to obtain the output.
+                return model(*args)
     finally:
         torch.onnx.utils._model_to_graph = old_model_to_graph
 
@@ -165,32 +154,29 @@ def _export(
     opset_ver = kwargs.get('opset_version', None)
     force_verbose = False
 
-    if pytorch_pfn_extras.requires("1.13.0"):
-        if "training" in kwargs and (isinstance(kwargs["training"], bool) or kwargs['training'] is None):
-            kwargs["training"] = torch.onnx.TrainingMode.TRAINING \
-                if kwargs["training"] \
-                else torch.onnx.TrainingMode.EVAL
+    if "training" in kwargs and (isinstance(kwargs["training"], bool) or kwargs['training'] is None):
+        kwargs["training"] = torch.onnx.TrainingMode.TRAINING \
+            if kwargs["training"] \
+            else torch.onnx.TrainingMode.EVAL
 
-    if pytorch_pfn_extras.requires('1.12.0'):
-        original_log = torch.onnx.log  # type: ignore[attr-defined]
+    original_log = torch.onnx.log  # type: ignore[attr-defined]
     if opset_ver is None:
         opset_ver = pytorch_pfn_extras.onnx._constants.onnx_default_opset
         kwargs['opset_version'] = opset_ver
-    if use_pfto or not pytorch_pfn_extras.requires('1.10.0'):
+    if use_pfto:
         strip_doc_string = kwargs.get('strip_doc_string', True)
         kwargs['strip_doc_string'] = False
     else:
         strip_doc_string = kwargs.pop('strip_doc_string', True)
         if not kwargs.get('verbose', False):
             force_verbose = True
-            if pytorch_pfn_extras.requires('1.12.0'):
-                #  Following line won't work because verbose mode always
-                # enable logging so we are replacing python function instead:
-                # torch.onnx.disable_log()
-                def no_op(*args: Any) -> None:
-                    pass
-
-                torch.onnx.log = no_op  # type: ignore[attr-defined]
+            #  Following line won't work because verbose mode always
+            # enable logging so we are replacing python function instead:
+            # torch.onnx.disable_log()
+            def no_op(*args: Any) -> None:
+                pass
+
+            torch.onnx.log = no_op  # type: ignore[attr-defined]
         kwargs['verbose'] = True
     # Exted args with kwargs (including default values)
     args = _decide_input_format(model, args)  # type: ignore[no-untyped-call]
@@ -223,9 +209,8 @@ def no_op(*args: Any) -> None:
         _strip_large_initializer_raw_data(onnx_graph, large_tensor_threshold)
 
     if force_verbose:
-        if pytorch_pfn_extras.requires('1.12.0'):
-            # torch.onnx.enable_log()
-            torch.onnx.log = original_log  # type: ignore[attr-defined]
+        # torch.onnx.enable_log()
+        torch.onnx.log = original_log  # type: ignore[attr-defined]
 
     return onnx_graph, outs