From 419d5d072375ee0044fecb94e4bfe21a7b3b0b9e Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Wed, 28 Sep 2016 00:15:58 -0800 Subject: Automated rollback of change 134501895 Change: 134506649 --- tensorflow/core/kernels/quantized_bias_add_op.cc | 89 ------------------------ 1 file changed, 89 deletions(-) delete mode 100644 tensorflow/core/kernels/quantized_bias_add_op.cc (limited to 'tensorflow/core/kernels/quantized_bias_add_op.cc') diff --git a/tensorflow/core/kernels/quantized_bias_add_op.cc b/tensorflow/core/kernels/quantized_bias_add_op.cc deleted file mode 100644 index 0b34bfcad8..0000000000 --- a/tensorflow/core/kernels/quantized_bias_add_op.cc +++ /dev/null @@ -1,89 +0,0 @@ -/* Copyright 2015 The TensorFlow Authors. All Rights Reserved. - -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. -==============================================================================*/ - -// Implements a quantized eight-bit version of the bias addition operation. - -#include "tensorflow/core/kernels/quantization_utils.h" -#include "tensorflow/core/framework/numeric_op.h" -#include "tensorflow/core/framework/op_kernel.h" -#include "tensorflow/core/framework/tensor.h" -#include "tensorflow/core/kernels/ops_util.h" -#include "tensorflow/core/lib/core/errors.h" - -namespace tensorflow { - -typedef Eigen::ThreadPoolDevice CPUDevice; - -template -class QuantizedBiasAddOp : public OpKernel { - public: - explicit QuantizedBiasAddOp(OpKernelConstruction* context) - : OpKernel(context) {} - - void Compute(OpKernelContext* context) override { - const Tensor& input = context->input(0); - const Tensor& bias = context->input(1); - const float input_min = context->input(2).flat()(0); - const float input_max = context->input(3).flat()(0); - const float bias_min = context->input(4).flat()(0); - const float bias_max = context->input(5).flat()(0); - - OP_REQUIRES(context, TensorShapeUtils::IsMatrixOrHigher(input.shape()), - errors::InvalidArgument("Input tensor must be at least 2D: ", - input.shape().DebugString())); - OP_REQUIRES(context, TensorShapeUtils::IsVector(bias.shape()), - errors::InvalidArgument("Biases must be 1D: ", - bias.shape().DebugString())); - const auto last_dim = input.shape().dims() - 1; - OP_REQUIRES( - context, bias.shape().dim_size(0) == input.shape().dim_size(last_dim), - errors::InvalidArgument( - "Must provide as many biases as the last dimension " - "of the input tensor: ", - bias.shape().DebugString(), " vs. ", input.shape().DebugString())); - - Tensor* output = nullptr; - OP_REQUIRES_OK(context, - context->allocate_output(0, input.shape(), &output)); - - float total_min; - float total_max; - QuantizedAddUsingEigen( - context->template eigen_device(), input, input_min, - input_max, bias, bias_min, bias_max, output, &total_min, &total_max); - - Tensor* output_min = nullptr; - OP_REQUIRES_OK(context, context->allocate_output(1, {}, &output_min)); - output_min->flat()(0) = total_min; - - Tensor* output_max = nullptr; - OP_REQUIRES_OK(context, context->allocate_output(2, {}, &output_max)); - output_max->flat()(0) = total_max; - } -}; - -REGISTER_KERNEL_BUILDER(Name("QuantizedBiasAdd") - .Device(DEVICE_CPU) - .TypeConstraint("T1") - .TypeConstraint("T2") - .TypeConstraint("out_type"), - QuantizedBiasAddOp); -REGISTER_KERNEL_BUILDER(Name("QuantizedBiasAdd") - .Device(DEVICE_CPU) - .TypeConstraint("T1") - .TypeConstraint("T2") - .TypeConstraint("out_type"), - QuantizedBiasAddOp); -} // namespace tensorflow -- cgit v1.2.3