COMPMID-3237: Implement NEQLSTMLayer
COMPMID-3082: Extend NEQLSTMLayer with enhancements
Change-Id: I88175b7bf69494a4eae510b74176fe8a0d6cd770
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2969
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-by: Sheri Zhang <sheri.zhang@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/runtime/common/LSTMParams.h b/arm_compute/runtime/common/LSTMParams.h
index f169457..e21ddd7 100644
--- a/arm_compute/runtime/common/LSTMParams.h
+++ b/arm_compute/runtime/common/LSTMParams.h
@@ -54,10 +54,10 @@
_output_layer_norm_weights(nullptr),
_cell_clip(0.f),
_projection_clip(0.0f),
- _input_gate_matmul_scale(0.0f),
- _forget_gate_matmul_scale(0.0f),
- _cell_gate_matmul_scale(0.0f),
- _output_gate_matmul_scale(0.0f),
+ _input_intermediate_scale(0.0f),
+ _forget_intermediate_scale(0.0f),
+ _cell_intermediate_scale(0.0f),
+ _output_intermediate_scale(0.0f),
_hidden_state_zero(0.0f),
_hidden_state_scale(0),
_has_peephole_opt(false),
@@ -74,10 +74,10 @@
~LSTMParams() = default;
/** Set CIFG tensor parameters.
*
- * @param[in] input_to_input_weights 2D weights tensor with dimensions [input_size, num_units]. Data types supported: F16/F32.
+ * @param[in] input_to_input_weights 2D weights tensor with dimensions [input_size, num_units]. Data types supported: QSYMM8/F16/F32.
* @param[in] recurrent_to_input_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input_to_input_weights.
* @param[in] cell_to_input_weights 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input_to_input_weights.
- * @param[in] input_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_to_input_weights
+ * @param[in] input_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_to_input_weights, S32 when @p input_to_input_weights is QSYMM8
*
* @return Reference to this LSTMParams object
*/
@@ -92,8 +92,8 @@
}
/** Set projection tensor parameters.
*
- * @param[in] projection_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Data types supported: F16/F32.
- * @param[in] projection_bias 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p projection_weights.
+ * @param[in] projection_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Data types supported: QSYMM8/F16/F32.
+ * @param[in] projection_bias 1D weights tensor with dimensions [output_size]. Data type supported: Same as @p projection_weights, S32 when @p input_to_input_weights is QSYMM8.
*
* @return Reference to this LSTMParams object
*/
@@ -106,8 +106,8 @@
}
/** Set peephole tensor parameters.
*
- * @param[in] cell_to_forget_weights 1D weights tensor with dimensions [num_units]. Data type supported: Data types supported: F16/F32.
- * @param[in] cell_to_output_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p cell_to_input_weights.
+ * @param[in] cell_to_forget_weights 1D weights tensor with dimensions [num_units]. Data type supported: Data types supported: QSYMM16/F16/F32.
+ * @param[in] cell_to_output_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p cell_to_forget_weights.
*
* @return Reference to this LSTMParams object
*/
@@ -120,7 +120,7 @@
}
/** Set layer normalization tensor parameters.
*
- * @param[in] input_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Data types supported: F16/F32.
+ * @param[in] input_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Data types supported: QSYMM16/F16/F32.
* @param[in] forget_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_layer_norm_weights.
* @param[in] cell_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_layer_norm_weights.
* @param[in] output_layer_norm_weights 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input_layer_norm_weights.
@@ -164,19 +164,19 @@
/** Set scale of the intermediate results of matmul of each layer parameters.
*
- * @param[in] input_gate_matmul_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at input gate.
- * @param[in] forget_gate_matmul_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at forget gate.
- * @param[in] cell_gate_matmul_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at cell gate.
- * @param[in] output_gate_matmul_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at output gate.
+ * @param[in] input_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at input gate.
+ * @param[in] forget_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at forget gate.
+ * @param[in] cell_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at cell gate.
+ * @param[in] output_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at output gate.
*
* @return Reference to this LSTMParams object
*/
- LSTMParams &set_matmul_scale_params(float input_gate_matmul_scale, float forget_gate_matmul_scale, float cell_gate_matmul_scale, float output_gate_matmul_scale)
+ LSTMParams &set_matmul_scale_params(float input_intermediate_scale, float forget_intermediate_scale, float cell_intermediate_scale, float output_intermediate_scale)
{
- _input_gate_matmul_scale = input_gate_matmul_scale;
- _forget_gate_matmul_scale = forget_gate_matmul_scale;
- _cell_gate_matmul_scale = cell_gate_matmul_scale;
- _output_gate_matmul_scale = output_gate_matmul_scale;
+ _input_intermediate_scale = input_intermediate_scale;
+ _forget_intermediate_scale = forget_intermediate_scale;
+ _cell_intermediate_scale = cell_intermediate_scale;
+ _output_intermediate_scale = output_intermediate_scale;
return *this;
}
@@ -187,7 +187,7 @@
*
* @return Reference to this LSTMParams object
*/
- LSTMParams &set_matmul_scale_params(int32_t hidden_state_zero, float hidden_state_scale)
+ LSTMParams &set_hidden_state_params(int32_t hidden_state_zero, float hidden_state_scale)
{
_hidden_state_zero = hidden_state_zero;
_hidden_state_scale = hidden_state_scale;
@@ -264,24 +264,24 @@
return _projection_clip;
}
- float input_gate_matmul_scale() const
+ float input_intermediate_scale() const
{
- return _input_gate_matmul_scale;
+ return _input_intermediate_scale;
}
- float forget_gate_matmul_scale() const
+ float forget_intermediate_scale() const
{
- return _forget_gate_matmul_scale;
+ return _forget_intermediate_scale;
}
- float cell_gate_matmul_scale() const
+ float cell_intermediate_scale() const
{
- return _cell_gate_matmul_scale;
+ return _cell_intermediate_scale;
}
- float output_gate_matmul_scale() const
+ float output_intermediate_scale() const
{
- return _output_gate_matmul_scale;
+ return _output_intermediate_scale;
}
int32_t hidden_state_zero() const
@@ -329,10 +329,10 @@
const T *_output_layer_norm_weights;
float _cell_clip;
float _projection_clip;
- float _input_gate_matmul_scale;
- float _forget_gate_matmul_scale;
- float _cell_gate_matmul_scale;
- float _output_gate_matmul_scale;
+ float _input_intermediate_scale;
+ float _forget_intermediate_scale;
+ float _cell_intermediate_scale;
+ float _output_intermediate_scale;
float _hidden_state_zero;
int32_t _hidden_state_scale;
bool _has_peephole_opt;