36 lines
1.5 KiB
C++
36 lines
1.5 KiB
C++
#pragma once
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// @generated by torchgen/gen.py from Function.h
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#include <ATen/Context.h>
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#include <ATen/DeviceGuard.h>
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#include <ATen/TensorUtils.h>
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#include <ATen/TracerMode.h>
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#include <ATen/core/Generator.h>
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#include <ATen/core/Reduction.h>
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#include <ATen/core/Tensor.h>
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#include <c10/core/Scalar.h>
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#include <c10/core/Storage.h>
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#include <c10/core/TensorOptions.h>
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#include <c10/util/Deprecated.h>
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#include <c10/util/Optional.h>
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#include <ATen/ops/gru_ops.h>
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namespace at {
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// aten::gru.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor)
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inline ::std::tuple<at::Tensor,at::Tensor> gru(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first) {
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return at::_ops::gru_input::call(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first);
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}
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// aten::gru.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor)
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inline ::std::tuple<at::Tensor,at::Tensor> gru(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional) {
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return at::_ops::gru_data::call(data, batch_sizes, hx, params, has_biases, num_layers, dropout, train, bidirectional);
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}
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}
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