Wafer_Inspection/Code/TestTRTInterDll/trtinfer_lib/common/dumpTFWts.py

#!/usr/bin/python
#
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# SPDX-License-Identifier: Apache-2.0
#
# 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
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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# Script to dump TensorFlow weights in TRT v1 and v2 dump format.
# The V1 format is for TensorRT 4.0. The V2 format is for TensorRT 4.0 and later.

import sys
import struct
import argparse

try:
    import tensorflow as tf
    from tensorflow.python import pywrap_tensorflow
except ImportError as err:
    sys.stderr.write("""Error: Failed to import module ({})""".format(err))
    sys.exit()

parser = argparse.ArgumentParser(description="TensorFlow Weight Dumper")

parser.add_argument(
    "-m",
    "--model",
    required=True,
    help="The checkpoint file basename, example basename(model.ckpt-766908.data-00000-of-00001) -> model.ckpt-766908",
)
parser.add_argument("-o", "--output", required=True, help="The weight file to dump all the weights to.")
parser.add_argument("-1", "--wtsv1", required=False, default=False, type=bool, help="Dump the weights in the wts v1.")

opt = parser.parse_args()

if opt.wtsv1:
    print("Outputting the trained weights in TensorRT's wts v1 format. This format is documented as:")
    print("Line 0: <number of buffers in the file>")
    print("Line 1-Num: [buffer name] [buffer type] [buffer size] <hex values>")
else:
    print("Outputting the trained weights in TensorRT's wts v2 format. This format is documented as:")
    print("Line 0: <number of buffers in the file>")
    print("Line 1-Num: [buffer name] [buffer type] [(buffer shape{e.g. (1, 2, 3)}] <buffer shaped size bytes of data>")

inputbase = opt.model
outputbase = opt.output


def float_to_hex(f):
    return hex(struct.unpack("<I", struct.pack("<f", f))[0])


def getTRTType(tensor):
    if tf.as_dtype(tensor.dtype) == tf.float32:
        return 0
    if tf.as_dtype(tensor.dtype) == tf.float16:
        return 1
    if tf.as_dtype(tensor.dtype) == tf.int8:
        return 2
    if tf.as_dtype(tensor.dtype) == tf.int32:
        return 3
    print("Tensor data type of %s is not supported in TensorRT" % (tensor.dtype))
    sys.exit()


try:
    # Open output file
    if opt.wtsv1:
        outputFileName = outputbase + ".wts"
    else:
        outputFileName = outputbase + ".wts2"
    outputFile = open(outputFileName, "w")

    # read vars from checkpoint
    reader = pywrap_tensorflow.NewCheckpointReader(inputbase)
    var_to_shape_map = reader.get_variable_to_shape_map()

    # Record count of weights
    count = 0
    for key in sorted(var_to_shape_map):
        count += 1
    outputFile.write("%s\n" % (count))

    # Dump the weights in either v1 or v2 format
    for key in sorted(var_to_shape_map):
        tensor = reader.get_tensor(key)
        file_key = key.replace("/", "_")
        typeOfElem = getTRTType(tensor)
        val = tensor.shape
        if opt.wtsv1:
            val = tensor.size
        print("%s %s %s " % (file_key, typeOfElem, val))
        flat_tensor = tensor.flatten()
        outputFile.write("%s 0 %s " % (file_key, val))
        if opt.wtsv1:
            for weight in flat_tensor:
                hexval = float_to_hex(float(weight))
                outputFile.write("%s " % (hexval[2:]))
        else:
            outputFile.write(flat_tensor.tobytes())
        outputFile.write("\n")
    outputFile.close()

except Exception as e:  # pylint: disable=broad-except
    print(str(e))
    if "corrupted compressed block contents" in str(e):
        print("It's likely that your checkpoint file has been compressed " "with SNAPPY.")
        if "Data loss" in str(e) and (any([e in inputbase for e in [".index", ".meta", ".data"]])):
            proposed_file = ".".join(inputbase.split(".")[0:-1])
            v2_file_error_template = """
           It's likely that this is a V2 checkpoint and you need to provide the filename
           *prefix*.  Try removing the '.' and extension.  Try:
           inspect checkpoint --file_name = {}"""
            print(v2_file_error_template.format(proposed_file))