Apply clang-format on repository
Code is formatted as per a revised clang format configuration
file(not part of this delivery). Version 14.0.6 is used.
Exclusion List:
- files with .cl extension
- files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...)
And the following directories
- compute_kernel_writer/validation/
- tests/
- include/
- src/core/NEON/kernels/convolution/
- src/core/NEON/kernels/arm_gemm/
- src/core/NEON/kernels/arm_conv/
- data/
There will be a follow up for formatting of .cl files and the
files under tests/ and compute_kernel_writer/validation/.
Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
diff --git a/examples/graph_deepspeech_v0_4_1.cpp b/examples/graph_deepspeech_v0_4_1.cpp
index da163b6..08cd4a4 100644
--- a/examples/graph_deepspeech_v0_4_1.cpp
+++ b/examples/graph_deepspeech_v0_4_1.cpp
@@ -23,6 +23,7 @@
*/
#include "arm_compute/graph.h"
#include "arm_compute/graph/Types.h"
+
#include "support/ToolchainSupport.h"
#include "utils/CommonGraphOptions.h"
#include "utils/GraphUtils.h"
@@ -37,8 +38,7 @@
class GraphDeepSpeechExample : public Example
{
public:
- GraphDeepSpeechExample()
- : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "DeepSpeech v0.4.1")
+ GraphDeepSpeechExample() : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "DeepSpeech v0.4.1")
{
}
bool do_setup(int argc, char **argv) override
@@ -51,7 +51,7 @@
common_params = consume_common_graph_parameters(common_opts);
// Return when help menu is requested
- if(common_params.help)
+ if (common_params.help)
{
cmd_parser.print_help(argv[0]);
return false;
@@ -64,7 +64,7 @@
std::string data_path = common_params.data_path;
const std::string model_path = "/cnn_data/deepspeech_model/";
- if(!data_path.empty())
+ if (!data_path.empty())
{
data_path += model_path;
}
@@ -77,131 +77,131 @@
const float cell_clip = 20.f;
// Create input descriptor
- const TensorShape tensor_shape = permute_shape(TensorShape(26U, 19U, n_steps, 1U), DataLayout::NHWC, common_params.data_layout);
- TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout);
+ const TensorShape tensor_shape =
+ permute_shape(TensorShape(26U, 19U, n_steps, 1U), DataLayout::NHWC, common_params.data_layout);
+ TensorDescriptor input_descriptor =
+ TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout);
// Set weights trained layout
const DataLayout weights_layout = DataLayout::NHWC;
- graph << common_params.target
- << common_params.fast_math_hint
+ graph << common_params.target << common_params.fast_math_hint
<< InputLayer(input_descriptor,
- get_weights_accessor(data_path, "input_values_x" + std::to_string(n_steps) + ".npy", weights_layout))
- .set_name("input_node");
+ get_weights_accessor(data_path, "input_values_x" + std::to_string(n_steps) + ".npy",
+ weights_layout))
+ .set_name("input_node");
- if(common_params.data_layout == DataLayout::NCHW)
+ if (common_params.data_layout == DataLayout::NCHW)
{
graph << PermuteLayer(PermutationVector(2U, 0U, 1U), common_params.data_layout).set_name("permute_to_nhwc");
}
graph << ReshapeLayer(TensorShape(494U, n_steps)).set_name("Reshape_input")
// Layer 1
- << FullyConnectedLayer(
- 2048U,
- get_weights_accessor(data_path, "h1_transpose.npy", weights_layout),
- get_weights_accessor(data_path, "MatMul_bias.npy"))
- .set_name("fc0")
+ << FullyConnectedLayer(2048U, get_weights_accessor(data_path, "h1_transpose.npy", weights_layout),
+ get_weights_accessor(data_path, "MatMul_bias.npy"))
+ .set_name("fc0")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, cell_clip))
- .set_name("Relu")
+ .set_name("Relu")
// Layer 2
- << FullyConnectedLayer(
- 2048U,
- get_weights_accessor(data_path, "h2_transpose.npy", weights_layout),
- get_weights_accessor(data_path, "MatMul_1_bias.npy"))
- .set_name("fc1")
+ << FullyConnectedLayer(2048U, get_weights_accessor(data_path, "h2_transpose.npy", weights_layout),
+ get_weights_accessor(data_path, "MatMul_1_bias.npy"))
+ .set_name("fc1")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, cell_clip))
- .set_name("Relu_1")
+ .set_name("Relu_1")
// Layer 3
- << FullyConnectedLayer(
- 2048U,
- get_weights_accessor(data_path, "h3_transpose.npy", weights_layout),
- get_weights_accessor(data_path, "MatMul_2_bias.npy"))
- .set_name("fc2")
+ << FullyConnectedLayer(2048U, get_weights_accessor(data_path, "h3_transpose.npy", weights_layout),
+ get_weights_accessor(data_path, "MatMul_2_bias.npy"))
+ .set_name("fc2")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, cell_clip))
- .set_name("Relu_2")
+ .set_name("Relu_2")
// Layer 4
<< ReshapeLayer(TensorShape(2048U, 1U, n_steps)).set_name("Reshape_1");
// Unstack Layer (using SplitLayerNode)
- NodeParams unstack_params = { "unstack", graph.hints().target_hint };
- NodeID unstack_nid = GraphBuilder::add_split_node(graph.graph(), unstack_params, { graph.tail_node(), 0 }, n_steps, 2);
+ NodeParams unstack_params = {"unstack", graph.hints().target_hint};
+ NodeID unstack_nid =
+ GraphBuilder::add_split_node(graph.graph(), unstack_params, {graph.tail_node(), 0}, n_steps, 2);
// Create input state descriptor
- TensorDescriptor state_descriptor = TensorDescriptor(TensorShape(2048U), common_params.data_type).set_layout(common_params.data_layout);
- SubStream previous_state(graph);
- SubStream add_y(graph);
+ TensorDescriptor state_descriptor =
+ TensorDescriptor(TensorShape(2048U), common_params.data_type).set_layout(common_params.data_layout);
+ SubStream previous_state(graph);
+ SubStream add_y(graph);
// Initial state for LSTM is all zeroes for both state_h and state_c, therefore only one input is created
- previous_state << InputLayer(state_descriptor,
- get_weights_accessor(data_path, "zeros.npy"))
- .set_name("previous_state_c_h");
- add_y << InputLayer(state_descriptor,
- get_weights_accessor(data_path, "ones.npy"))
- .set_name("add_y");
+ previous_state << InputLayer(state_descriptor, get_weights_accessor(data_path, "zeros.npy"))
+ .set_name("previous_state_c_h");
+ add_y << InputLayer(state_descriptor, get_weights_accessor(data_path, "ones.npy")).set_name("add_y");
// Create LSTM Fully Connected weights and bias descriptors
- TensorDescriptor lstm_weights_descriptor = TensorDescriptor(TensorShape(4096U, 8192U), common_params.data_type).set_layout(common_params.data_layout);
- TensorDescriptor lstm_bias_descriptor = TensorDescriptor(TensorShape(8192U), common_params.data_type).set_layout(common_params.data_layout);
- SubStream lstm_fc_weights(graph);
- SubStream lstm_fc_bias(graph);
- lstm_fc_weights << ConstantLayer(lstm_weights_descriptor,
- get_weights_accessor(data_path, "rnn_lstm_cell_kernel_transpose.npy", weights_layout))
- .set_name("h5/transpose");
+ TensorDescriptor lstm_weights_descriptor =
+ TensorDescriptor(TensorShape(4096U, 8192U), common_params.data_type).set_layout(common_params.data_layout);
+ TensorDescriptor lstm_bias_descriptor =
+ TensorDescriptor(TensorShape(8192U), common_params.data_type).set_layout(common_params.data_layout);
+ SubStream lstm_fc_weights(graph);
+ SubStream lstm_fc_bias(graph);
+ lstm_fc_weights << ConstantLayer(
+ lstm_weights_descriptor,
+ get_weights_accessor(data_path, "rnn_lstm_cell_kernel_transpose.npy", weights_layout))
+ .set_name("h5/transpose");
lstm_fc_bias << ConstantLayer(lstm_bias_descriptor,
get_weights_accessor(data_path, "rnn_lstm_cell_MatMul_bias.npy"))
- .set_name("MatMul_3_bias");
+ .set_name("MatMul_3_bias");
// LSTM Block
- std::pair<SubStream, SubStream> new_state_1 = add_lstm_cell(unstack_nid, 0, previous_state, previous_state, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_2 = add_lstm_cell(unstack_nid, 1, new_state_1.first, new_state_1.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_3 = add_lstm_cell(unstack_nid, 2, new_state_2.first, new_state_2.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_4 = add_lstm_cell(unstack_nid, 3, new_state_3.first, new_state_3.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_5 = add_lstm_cell(unstack_nid, 4, new_state_4.first, new_state_4.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_6 = add_lstm_cell(unstack_nid, 5, new_state_5.first, new_state_5.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_7 = add_lstm_cell(unstack_nid, 6, new_state_6.first, new_state_6.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_8 = add_lstm_cell(unstack_nid, 7, new_state_7.first, new_state_7.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_9 = add_lstm_cell(unstack_nid, 8, new_state_8.first, new_state_8.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_10 = add_lstm_cell(unstack_nid, 9, new_state_9.first, new_state_9.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_11 = add_lstm_cell(unstack_nid, 10, new_state_10.first, new_state_10.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_12 = add_lstm_cell(unstack_nid, 11, new_state_11.first, new_state_11.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_13 = add_lstm_cell(unstack_nid, 12, new_state_12.first, new_state_12.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_14 = add_lstm_cell(unstack_nid, 13, new_state_13.first, new_state_13.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_15 = add_lstm_cell(unstack_nid, 14, new_state_14.first, new_state_14.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_16 = add_lstm_cell(unstack_nid, 15, new_state_15.first, new_state_15.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_1 =
+ add_lstm_cell(unstack_nid, 0, previous_state, previous_state, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_2 =
+ add_lstm_cell(unstack_nid, 1, new_state_1.first, new_state_1.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_3 =
+ add_lstm_cell(unstack_nid, 2, new_state_2.first, new_state_2.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_4 =
+ add_lstm_cell(unstack_nid, 3, new_state_3.first, new_state_3.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_5 =
+ add_lstm_cell(unstack_nid, 4, new_state_4.first, new_state_4.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_6 =
+ add_lstm_cell(unstack_nid, 5, new_state_5.first, new_state_5.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_7 =
+ add_lstm_cell(unstack_nid, 6, new_state_6.first, new_state_6.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_8 =
+ add_lstm_cell(unstack_nid, 7, new_state_7.first, new_state_7.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_9 =
+ add_lstm_cell(unstack_nid, 8, new_state_8.first, new_state_8.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_10 =
+ add_lstm_cell(unstack_nid, 9, new_state_9.first, new_state_9.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_11 = add_lstm_cell(
+ unstack_nid, 10, new_state_10.first, new_state_10.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_12 = add_lstm_cell(
+ unstack_nid, 11, new_state_11.first, new_state_11.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_13 = add_lstm_cell(
+ unstack_nid, 12, new_state_12.first, new_state_12.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_14 = add_lstm_cell(
+ unstack_nid, 13, new_state_13.first, new_state_13.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_15 = add_lstm_cell(
+ unstack_nid, 14, new_state_14.first, new_state_14.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_16 = add_lstm_cell(
+ unstack_nid, 15, new_state_15.first, new_state_15.second, add_y, lstm_fc_weights, lstm_fc_bias);
// Concatenate new states on height
const int axis = 1;
- graph << StackLayer(axis,
- std::move(new_state_1.second),
- std::move(new_state_2.second),
- std::move(new_state_3.second),
- std::move(new_state_4.second),
- std::move(new_state_5.second),
- std::move(new_state_6.second),
- std::move(new_state_7.second),
- std::move(new_state_8.second),
- std::move(new_state_9.second),
- std::move(new_state_10.second),
- std::move(new_state_11.second),
- std::move(new_state_12.second),
- std::move(new_state_13.second),
- std::move(new_state_14.second),
- std::move(new_state_15.second),
- std::move(new_state_16.second))
- .set_name("concat");
+ graph << StackLayer(axis, std::move(new_state_1.second), std::move(new_state_2.second),
+ std::move(new_state_3.second), std::move(new_state_4.second), std::move(new_state_5.second),
+ std::move(new_state_6.second), std::move(new_state_7.second), std::move(new_state_8.second),
+ std::move(new_state_9.second), std::move(new_state_10.second),
+ std::move(new_state_11.second), std::move(new_state_12.second),
+ std::move(new_state_13.second), std::move(new_state_14.second),
+ std::move(new_state_15.second), std::move(new_state_16.second))
+ .set_name("concat");
- graph << FullyConnectedLayer(
- 2048U,
- get_weights_accessor(data_path, "h5_transpose.npy", weights_layout),
- get_weights_accessor(data_path, "MatMul_3_bias.npy"))
- .set_name("fc3")
+ graph << FullyConnectedLayer(2048U, get_weights_accessor(data_path, "h5_transpose.npy", weights_layout),
+ get_weights_accessor(data_path, "MatMul_3_bias.npy"))
+ .set_name("fc3")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, cell_clip))
- .set_name("Relu3")
- << FullyConnectedLayer(
- 29U,
- get_weights_accessor(data_path, "h6_transpose.npy", weights_layout),
- get_weights_accessor(data_path, "MatMul_4_bias.npy"))
- .set_name("fc3")
+ .set_name("Relu3")
+ << FullyConnectedLayer(29U, get_weights_accessor(data_path, "h6_transpose.npy", weights_layout),
+ get_weights_accessor(data_path, "MatMul_4_bias.npy"))
+ .set_name("fc3")
<< SoftmaxLayer().set_name("logits");
graph << OutputLayer(get_output_accessor(common_params, 5));
@@ -241,7 +241,7 @@
return Status{};
}
- std::pair<SubStream, SubStream> add_lstm_cell(NodeID unstack_nid,
+ std::pair<SubStream, SubStream> add_lstm_cell(NodeID unstack_nid,
unsigned int unstack_idx,
SubStream previous_state_c,
SubStream previous_state_h,
@@ -250,41 +250,41 @@
SubStream lstm_fc_bias)
{
const std::string cell_name("rnn/lstm_cell_" + std::to_string(unstack_idx));
- const DataLayoutDimension concat_dim = (common_params.data_layout == DataLayout::NHWC) ? DataLayoutDimension::CHANNEL : DataLayoutDimension::WIDTH;
+ const DataLayoutDimension concat_dim =
+ (common_params.data_layout == DataLayout::NHWC) ? DataLayoutDimension::CHANNEL : DataLayoutDimension::WIDTH;
// Concatenate result of Unstack with previous_state_h
- NodeParams concat_params = { cell_name + "/concat", graph.hints().target_hint };
+ NodeParams concat_params = {cell_name + "/concat", graph.hints().target_hint};
NodeID concat_nid = graph.graph().add_node<ConcatenateLayerNode>(2, concat_dim);
graph.graph().add_connection(unstack_nid, unstack_idx, concat_nid, 0);
graph.graph().add_connection(previous_state_h.tail_node(), 0, concat_nid, 1);
set_node_params(graph.graph(), concat_nid, concat_params);
graph.forward_tail(concat_nid);
- graph << FullyConnectedLayer(
- 8192U,
- lstm_fc_weights,
- lstm_fc_bias)
- .set_name(cell_name + "/BiasAdd");
+ graph << FullyConnectedLayer(8192U, lstm_fc_weights, lstm_fc_bias).set_name(cell_name + "/BiasAdd");
// Split Layer
const unsigned int num_splits = 4;
const unsigned int split_axis = 0;
- NodeParams split_params = { cell_name + "/split", graph.hints().target_hint };
- NodeID split_nid = GraphBuilder::add_split_node(graph.graph(), split_params, { graph.tail_node(), 0 }, num_splits, split_axis);
+ NodeParams split_params = {cell_name + "/split", graph.hints().target_hint};
+ NodeID split_nid =
+ GraphBuilder::add_split_node(graph.graph(), split_params, {graph.tail_node(), 0}, num_splits, split_axis);
- NodeParams sigmoid_1_params = { cell_name + "/Sigmoid_1", graph.hints().target_hint };
- NodeParams add_params = { cell_name + "/add", graph.hints().target_hint };
- NodeParams sigmoid_2_params = { cell_name + "/Sigmoid_2", graph.hints().target_hint };
- NodeParams tanh_params = { cell_name + "/Tanh", graph.hints().target_hint };
+ NodeParams sigmoid_1_params = {cell_name + "/Sigmoid_1", graph.hints().target_hint};
+ NodeParams add_params = {cell_name + "/add", graph.hints().target_hint};
+ NodeParams sigmoid_2_params = {cell_name + "/Sigmoid_2", graph.hints().target_hint};
+ NodeParams tanh_params = {cell_name + "/Tanh", graph.hints().target_hint};
// Sigmoid 1 (first split)
- NodeID sigmoid_1_nid = graph.graph().add_node<ActivationLayerNode>(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC));
+ NodeID sigmoid_1_nid = graph.graph().add_node<ActivationLayerNode>(
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC));
graph.graph().add_connection(split_nid, 0, sigmoid_1_nid, 0);
set_node_params(graph.graph(), sigmoid_1_nid, sigmoid_1_params);
// Tanh (second split)
- NodeID tanh_nid = graph.graph().add_node<ActivationLayerNode>(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH, 1.f, 1.f));
+ NodeID tanh_nid = graph.graph().add_node<ActivationLayerNode>(
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH, 1.f, 1.f));
graph.graph().add_connection(split_nid, 1, tanh_nid, 0);
set_node_params(graph.graph(), tanh_nid, tanh_params);
@@ -292,13 +292,15 @@
tanh_ss.forward_tail(tanh_nid);
// Add (third split)
- NodeID add_nid = graph.graph().add_node<EltwiseLayerNode>(descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add });
+ NodeID add_nid =
+ graph.graph().add_node<EltwiseLayerNode>(descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add});
graph.graph().add_connection(split_nid, 2, add_nid, 0);
graph.graph().add_connection(add_y.tail_node(), 0, add_nid, 1);
set_node_params(graph.graph(), add_nid, add_params);
// Sigmoid 2 (fourth split)
- NodeID sigmoid_2_nid = graph.graph().add_node<ActivationLayerNode>(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC));
+ NodeID sigmoid_2_nid = graph.graph().add_node<ActivationLayerNode>(
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC));
graph.graph().add_connection(split_nid, 3, sigmoid_2_nid, 0);
set_node_params(graph.graph(), sigmoid_2_nid, sigmoid_2_params);
@@ -306,28 +308,28 @@
sigmoid_1_ss.forward_tail(sigmoid_1_nid);
SubStream mul_1_ss(sigmoid_1_ss);
mul_1_ss << EltwiseLayer(std::move(sigmoid_1_ss), std::move(tanh_ss), EltwiseOperation::Mul)
- .set_name(cell_name + "/mul_1");
+ .set_name(cell_name + "/mul_1");
SubStream tanh_1_ss_tmp(graph);
tanh_1_ss_tmp.forward_tail(add_nid);
tanh_1_ss_tmp << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC))
- .set_name(cell_name + "/Sigmoid");
+ .set_name(cell_name + "/Sigmoid");
SubStream tanh_1_ss_tmp2(tanh_1_ss_tmp);
tanh_1_ss_tmp2 << EltwiseLayer(std::move(tanh_1_ss_tmp), std::move(previous_state_c), EltwiseOperation::Mul)
- .set_name(cell_name + "/mul");
+ .set_name(cell_name + "/mul");
SubStream tanh_1_ss(tanh_1_ss_tmp2);
tanh_1_ss << EltwiseLayer(std::move(tanh_1_ss_tmp2), std::move(mul_1_ss), EltwiseOperation::Add)
- .set_name(cell_name + "/new_state_c");
+ .set_name(cell_name + "/new_state_c");
SubStream new_state_c(tanh_1_ss);
tanh_1_ss << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH, 1.f, 1.f))
- .set_name(cell_name + "/Tanh_1");
+ .set_name(cell_name + "/Tanh_1");
SubStream sigmoid_2_ss(graph);
sigmoid_2_ss.forward_tail(sigmoid_2_nid);
graph << EltwiseLayer(std::move(sigmoid_2_ss), std::move(tanh_1_ss), EltwiseOperation::Mul)
- .set_name(cell_name + "/new_state_h");
+ .set_name(cell_name + "/new_state_h");
SubStream new_state_h(graph);
return std::pair<SubStream, SubStream>(new_state_c, new_state_h);