ca3e7f55d9
This CL adds experimental enable_numeric_verify in TFLite converter.mlir_quantize() for quantization numeric verification. This pass adds NumericVerify ops for debugging during full-integer quantization, and NumericVerify op will output the differences between the original float & the dequantized values of the quantized values. The main characteristic of NumericVerify op is the output tensor name has the following format:
NumericVerify/{tensor_name}:{tensor_id}
where tensor_name and tensor_id are from the original quantized op's activation tensor (the first input tensor of the NumericVerify op) for the purpose of debugging. It provides users the easy way to search for tensors in the debugging tools.
If you turn on log_if_failed in NumericVerify op, then it will output logs & throw errors when there exist any errors > tolerance.
PiperOrigin-RevId: 348740984
Change-Id: Ifb965d2237e827a747d1888cbd21af311d42e4a1
65 lines
2.6 KiB
Python
65 lines
2.6 KiB
Python
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Wraps toco interface with python lazy loader."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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# We need to import pywrap_tensorflow prior to the toco wrapper.
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# pylint: disable=invalid-import-order,g-bad-import-order
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from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
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from tensorflow.python import _pywrap_toco_api
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# TODO(b/137402359): Remove lazy loading wrapper
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def wrapped_toco_convert(model_flags_str, toco_flags_str, input_data_str,
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debug_info_str, enable_mlir_converter):
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"""Wraps TocoConvert with lazy loader."""
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return _pywrap_toco_api.TocoConvert(
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model_flags_str,
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toco_flags_str,
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input_data_str,
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False, # extended_return
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debug_info_str,
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enable_mlir_converter)
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def wrapped_get_potentially_supported_ops():
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"""Wraps TocoGetPotentiallySupportedOps with lazy loader."""
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return _pywrap_toco_api.TocoGetPotentiallySupportedOps()
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def wrapped_experimental_mlir_quantize(input_data_str, disable_per_channel,
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fully_quantize, inference_type,
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enable_numeric_verify):
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"""Wraps experimental mlir quantize model."""
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return _pywrap_toco_api.ExperimentalMlirQuantizeModel(input_data_str,
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disable_per_channel,
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fully_quantize,
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inference_type,
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enable_numeric_verify)
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def wrapped_experimental_mlir_sparsify(input_data_str):
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"""Wraps experimental mlir sparsify model."""
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return _pywrap_toco_api.ExperimentalMlirSparsifyModel(input_data_str)
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def wrapped_register_custom_opdefs(custom_opdefs_list):
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"""Wraps RegisterCustomOpdefs with lazy loader."""
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return _pywrap_toco_api.RegisterCustomOpdefs(custom_opdefs_list)
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