wehub-resource-sync
109 lines
4.9 KiB
C++
109 lines
4.9 KiB
C++
/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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// This file is MACHINE GENERATED! Do not edit.
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#ifndef TENSORFLOW_C_EXPERIMENTAL_OPS_MATH_OPS_H_
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#define TENSORFLOW_C_EXPERIMENTAL_OPS_MATH_OPS_H_
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#include "absl/status/status.h"
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#include "tensorflow/c/eager/abstract_context.h"
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#include "tensorflow/c/eager/abstract_tensor_handle.h"
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#include "tensorflow/core/framework/types.h" // NOLINT
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namespace tensorflow {
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namespace ops {
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// Returns x * y element-wise.
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absl::Status Mul(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle* const y, AbstractTensorHandle** z,
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const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Returns the complex conjugate of a complex number.
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absl::Status Conj(AbstractContext* ctx, AbstractTensorHandle* const input,
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AbstractTensorHandle** output, const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Returns x + y element-wise.
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absl::Status AddV2(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle* const y, AbstractTensorHandle** z,
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const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Multiply the matrix "a" by the matrix "b".
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absl::Status MatMul(AbstractContext* ctx, AbstractTensorHandle* const a,
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AbstractTensorHandle* const b,
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AbstractTensorHandle** product, bool transpose_a = false,
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bool transpose_b = false, bool grad_a = false,
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bool grad_b = false, const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Computes numerical negative value element-wise.
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absl::Status Neg(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle** y, const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Computes the sum of elements across dimensions of a tensor.
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absl::Status Sum(AbstractContext* ctx, AbstractTensorHandle* const input,
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AbstractTensorHandle* const reduction_indices,
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AbstractTensorHandle** output, bool keep_dims = false,
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const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Returns x - y element-wise.
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absl::Status Sub(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle* const y, AbstractTensorHandle** z,
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const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Returns x / y element-wise.
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absl::Status Div(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle* const y, AbstractTensorHandle** z,
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const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Returns 0 if the denominator is zero.
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absl::Status DivNoNan(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle* const y, AbstractTensorHandle** z,
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const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Computes exponential of x element-wise. \\(y = e^x\\).
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absl::Status Exp(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle** y, const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Computes square root of x element-wise.
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absl::Status Sqrt(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle** y, const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Computes the gradient for the sqrt of `x` wrt its input.
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absl::Status SqrtGrad(AbstractContext* ctx, AbstractTensorHandle* const y,
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AbstractTensorHandle* const dy, AbstractTensorHandle** z,
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const char* name = nullptr,
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const char* raw_device_name = nullptr);
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// Computes natural logarithm of (1 + x) element-wise.
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absl::Status Log1p(AbstractContext* ctx, AbstractTensorHandle* const x,
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AbstractTensorHandle** y, const char* name = nullptr,
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const char* raw_device_name = nullptr);
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} // namespace ops
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} // namespace tensorflow
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#endif // TENSORFLOW_C_EXPERIMENTAL_OPS_MATH_OPS_H_
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