inference.sh

#!/usr/bin/env bash
#
# Copyright (c) 2020 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

MODEL_DIR=${MODEL_DIR-$PWD}

if [ -z "${OUTPUT_DIR}" ]; then
  echo "The required environment variable OUTPUT_DIR has not been set"
  exit 1
fi

# Create the output directory in case it doesn't already exist
mkdir -p ${OUTPUT_DIR}

if [ -z "${PRECISION}" ]; then
  echo "The required environment variable PRECISION has not been set"
  echo "Please set PRECISION to fp32, int8, or bfloat16."
  exit 1
fi

if [[ $PRECISION != "fp32" ]] && [[ $PRECISION != "int8" ]] && [[ $PRECISION != "bfloat16" ]]; then
  echo "The specified precision '${PRECISION}' is unsupported."
  echo "Supported precisions are: fp32, bfloat16, and int8"
  exit 1
fi

if [ -z "${TF_MODELS_DIR}" ]; then
  echo "The required environment variable TF_MODELS_DIR has not been set."
  echo "Set TF_MODELS_DIR to the directory where the tensorflow/models repo has been cloned."
  exit 1
fi

if [ ! -d "${TF_MODELS_DIR}" ]; then
  echo "The TF_MODELS_DIR directory '${TF_MODELS_DIR}' does not exist"
  exit 1
fi

if [ -z "${PRETRAINED_MODEL}" ]; then
    if [[ $PRECISION == "int8" ]]; then
        PRETRAINED_MODEL="${MODEL_DIR}/pretrained_model/ssd_resnet34_int8_bs1_pretrained_model.pb"
    elif [[ $PRECISION == "bfloat16" || $PRECISION == "fp32" ]]; then
        PRETRAINED_MODEL="${MODEL_DIR}/pretrained_model/ssd_resnet34_fp32_bs1_pretrained_model.pb"
    else
        echo "The specified precision '${PRECISION}' is unsupported."
        echo "Supported precisions are: fp32, bfloat16, and int8"
        exit 1
    fi
    if [[ ! -f "${PRETRAINED_MODEL}" ]]; then
    echo "The pretrained model could not be found. Please set the PRETRAINED_MODEL env var to point to the frozen graph file."
    exit 1
    fi
elif [[ ! -f "${PRETRAINED_MODEL}" ]]; then
  echo "The file specified by the PRETRAINED_MODEL environment variable (${PRETRAINED_MODEL}) does not exist."
  exit 1
fi

export PYTHONPATH=${PYTHONPATH}:${TF_MODELS_DIR}/research
export PYTHONPATH=${PYTHONPATH}:${TF_BENCHMARKS_DIR}/scripts/tf_cnn_benchmarks

# If batch size env is not mentioned, then the workload will run with the default batch size.
if [ -z "${BATCH_SIZE}"]; then
  BATCH_SIZE="1"
  echo "Running with default batch size of ${BATCH_SIZE}"
fi

source "${MODEL_DIR}/quickstart/common/utils.sh"
_command python ${MODEL_DIR}/benchmarks/launch_benchmark.py \
    --in-graph $PRETRAINED_MODEL \
    --model-source-dir $TF_MODELS_DIR \
    --model-name ssd-resnet34 \
    --framework tensorflow \
    --precision ${PRECISION} \
    --mode inference \
    --socket-id 0 \
    --batch-size ${BATCH_SIZE} \
    --benchmark-only \
    --output-dir ${OUTPUT_DIR} \
    $@