COMPMID-1923: Input is ignored if peephole optimization is enabled in
LSTM
Change-Id: I9e6c4fe279aafaf7f77af453785a8f677868a25a
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/639
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/runtime/NEON/functions/NELSTMLayer.cpp b/src/runtime/NEON/functions/NELSTMLayer.cpp
index 2a2980b..73afd05 100644
--- a/src/runtime/NEON/functions/NELSTMLayer.cpp
+++ b/src/runtime/NEON/functions/NELSTMLayer.cpp
@@ -111,8 +111,8 @@
_forget_gate_out2.allocator()->allocate();
_memory_group.manage(&_forget_gate_out5);
_accum_forget_gate1.configure(&_forget_gate_out1, &_forget_gate_out3, &_forget_gate_out5, ConvertPolicy::SATURATE);
+ _forget_gate_out1.allocator()->allocate();
Tensor *forget_gate_out = &_forget_gate_out5;
-
if(lstm_params.has_peephole_opt())
{
_forget_gate_out4.allocator()->init(TensorInfo(cell_state_shape, 1, input->info()->data_type()));
@@ -129,18 +129,19 @@
{
_forget_gate_out3.allocator()->allocate();
}
- _activation_forget_gate.configure(forget_gate_out, &_forget_gate_out1, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC));
+ _activation_forget_gate.configure(forget_gate_out, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC));
forget_gate_out->allocator()->allocate();
// Configure block that calculates the input gate
// input_gate = Activation(input * input_to_input_weights + output_state * recurrent_to_input_weights + PixelWiseMul(cell_state, cell_to_input_weights) + input_gate_bias), without CIFG
// input_gate = 1 - forget_gate, with CIFG
_input_gate_out1.allocator()->init(TensorInfo(cell_state_shape, 1, input->info()->data_type()));
+ Tensor *input_gate_out = &_input_gate_out1;
if(lstm_params.has_cifg_opt())
{
_memory_group.manage(&_input_gate_out1);
_ones.allocator()->init(TensorInfo(cell_state_shape, 1, input->info()->data_type()));
- _subtract_input_gate.configure(&_ones, &_forget_gate_out1, &_input_gate_out1, ConvertPolicy::SATURATE);
+ _subtract_input_gate.configure(&_ones, forget_gate_out, &_input_gate_out1, ConvertPolicy::SATURATE);
_ones.allocator()->allocate();
_run_cifg_opt = true;
}
@@ -162,16 +163,22 @@
_input_gate_out2.allocator()->allocate();
_memory_group.manage(&_input_gate_out4);
_accum_input_gate1.configure(&_input_gate_out1, &_input_gate_out3, &_input_gate_out4, ConvertPolicy::SATURATE);
+ _input_gate_out3.allocator()->allocate();
+ input_gate_out = &_input_gate_out4;
if(_run_peephole_opt)
{
_memory_group.manage(&_input_gate_out5);
_pixelwise_mul_input_gate.configure(cell_state_in, lstm_params.cell_to_input_weights(), &_input_gate_out5, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO);
_accum_input_gate2.configure(&_input_gate_out4, &_input_gate_out5, &_input_gate_out1, ConvertPolicy::SATURATE);
+ _input_gate_out4.allocator()->allocate();
_input_gate_out5.allocator()->allocate();
+ input_gate_out = &_input_gate_out1;
}
- _input_gate_out3.allocator()->allocate();
- _input_gate_out4.allocator()->allocate();
- _activation_input_gate.configure(&_input_gate_out1, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC));
+ else
+ {
+ _input_gate_out1.allocator()->allocate();
+ }
+ _activation_input_gate.configure(input_gate_out, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC));
}
// Configure block that calculates the cell state
@@ -194,11 +201,9 @@
_accum_cell_state1.configure(&_cell_state_out1, &_cell_state_out3, &_cell_state_out4, ConvertPolicy::SATURATE);
_activation_cell_state.configure(&_cell_state_out4, nullptr, activation_info);
_memory_group.manage(&_cell_state_out5);
- _pixelwise_mul_cell_state1.configure(&_cell_state_out4, &_input_gate_out1, &_cell_state_out5, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO);
- _input_gate_out1.allocator()->allocate();
+ _pixelwise_mul_cell_state1.configure(&_cell_state_out4, input_gate_out, &_cell_state_out5, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO);
_cell_state_out4.allocator()->allocate();
- _pixelwise_mul_cell_state2.configure(&_forget_gate_out1, cell_state_in, &_cell_state_out3, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO);
- _forget_gate_out1.allocator()->allocate();
+ _pixelwise_mul_cell_state2.configure(forget_gate_out, cell_state_in, &_cell_state_out3, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO);
_accum_cell_state2.configure(&_cell_state_out5, &_cell_state_out3, &_cell_state_out1, ConvertPolicy::SATURATE);
_cell_state_out3.allocator()->allocate();
_cell_state_out5.allocator()->allocate();
@@ -281,19 +286,22 @@
// Copy cell state and output
_copy_cell_state.configure(&_cell_state_out1, cell_state_out);
- _cell_state_out1.allocator()->allocate();
_copy_output.configure(output_state_out, output);
// Vector for holding the tensors to store in scratch buffer
std::vector<ITensor *> scratch_inputs;
if(!lstm_params.has_cifg_opt())
{
- scratch_inputs.emplace_back(&_input_gate_out1);
+ scratch_inputs.emplace_back(input_gate_out);
}
scratch_inputs.emplace_back(&_cell_state_out1);
scratch_inputs.emplace_back(forget_gate_out);
scratch_inputs.emplace_back(output_gate_out);
_concat_scratch_buffer.configure(scratch_inputs, scratch_buffer);
+ input_gate_out->allocator()->allocate();
+ _cell_state_out1.allocator()->allocate();
+ forget_gate_out->allocator()->allocate();
+ output_gate_out->allocator()->allocate();
}
Status NELSTMLayer::validate(const ITensorInfo *input,