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authorMichalis Spyrou <michalis.spyrou@arm.com>2018-06-05 11:45:48 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:53:09 +0000
commit542e92d95536f2ab7fc6f1cc1aa1bd4f1d471212 (patch)
treea4c03807d9731c1305b6f446282d3f4b97cfb595 /arm_compute/runtime/NEON/functions/NERNNLayer.h
parent72219330fd85b1271e714d4ba894d6d8e26340c9 (diff)
downloadComputeLibrary-542e92d95536f2ab7fc6f1cc1aa1bd4f1d471212.tar.gz
COMPMID-1067 NEON RNN FP32 / FP16
Change-Id: I440df2b2af512fd874651baf28428caa6f8e0b41 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/134433 Tested-by: Jenkins <bsgcomp@arm.com> Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
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+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef __ARM_COMPUTE_NERNNLAYER_H__
+#define __ARM_COMPUTE_NERNNLAYER_H__
+
+#include "arm_compute/core/NEON/kernels/NEActivationLayerKernel.h"
+#include "arm_compute/core/NEON/kernels/NEArithmeticAdditionKernel.h"
+#include "arm_compute/runtime/NEON/INESimpleFunction.h"
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEGEMM.h"
+
+namespace arm_compute
+{
+// Forward declarations
+class ITensor;
+
+/** Basic function to run @ref NERNNLayer */
+class NERNNLayer : public IFunction
+{
+public:
+ /** Default constructor */
+ NERNNLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ NERNNLayer(const NERNNLayer &) = delete;
+ /** Default move constructor */
+ NERNNLayer(NERNNLayer &&) = default;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ NERNNLayer &operator=(const NERNNLayer &) = delete;
+ /** Default move assignment operator */
+ NERNNLayer &operator=(NERNNLayer &&) = default;
+ /** Initialize the function
+ *
+ * @param[in] input Input is a 2-D tensor of shape [input_size, batch_size]. Data types supported: F16/F32
+ * @param[in] weights Weights tensor of shape [input_size, num_units] that multiplies the input. Data types supported: Same as @p input
+ * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the current 'state'. Data types supported: Same as @p input
+ * @param[in] bias Bias vector of shape [num_units]. Data types supported: Same as @p input
+ * @param[out] output Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input
+ * @param[in,out] hidden_state Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input
+ * @param[in] info Activation layer parameter.
+ */
+ void configure(const ITensor *input, const ITensor *weights, const ITensor *recurrent_weights, const ITensor *bias, ITensor *hidden_state, ITensor *output, ActivationLayerInfo &info);
+ /** Initialize the function
+ *
+ * @param[in] input Input is a 2-D tensor of shape [input_size, batch_size]. Data types supported: F16/F32
+ * @param[in] weights Weights tensor of shape [input_size, num_units] that multiplies the input. Data types supported: Same as @p input
+ * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the current 'state'. Data types supported: Same as @p input
+ * @param[in] bias Bias vector of shape [num_units]. Data types supported: Same as @p input
+ * @param[in] output Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input
+ * @param[in] hidden_state Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input
+ * @param[in] info Activation layer parameter.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *recurrent_weights, const ITensorInfo *bias, const ITensorInfo *hidden_state, const ITensorInfo *output,
+ const ActivationLayerInfo &info);
+
+ // Inherited methods overridden:
+ void run() override;
+
+private:
+ MemoryGroup _memory_group;
+ NEGEMM _gemm_state_f;
+ NEArithmeticAdditionKernel _add_kernel;
+ NEActivationLayerKernel _activation_kernel;
+ NEFullyConnectedLayer _fully_connected_kernel;
+ Tensor _fully_connected_out;
+ Tensor _gemm_output;
+ Tensor _add_output;
+ ITensor *_hidden_state;
+ ITensor *_output;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_NERNNLAYER_H__ */