From ee4833d0a16cd65ad4fa9de087ec92080716e996 Mon Sep 17 00:00:00 2001 From: Sang-Hoon Park Date: Wed, 20 May 2020 09:13:32 +0100 Subject: COMPMID-3497: Add checks for zero scale values to QLSTMLayer Checks are added to validate() function to check both for configuration and validation call. Change-Id: I2ae9a92a5d90112f5b41befc4ce655ff9451d150 Signed-off-by: Sang-Hoon Park Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3227 Reviewed-by: Michele Di Giorgio Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins --- src/runtime/CL/functions/CLQLSTMLayer.cpp | 6 ++++++ 1 file changed, 6 insertions(+) (limited to 'src/runtime/CL/functions/CLQLSTMLayer.cpp') diff --git a/src/runtime/CL/functions/CLQLSTMLayer.cpp b/src/runtime/CL/functions/CLQLSTMLayer.cpp index 60e42a500d..a8edd5d98d 100644 --- a/src/runtime/CL/functions/CLQLSTMLayer.cpp +++ b/src/runtime/CL/functions/CLQLSTMLayer.cpp @@ -672,6 +672,7 @@ Status CLQLSTMLayer::validate(const ITensorInfo *input, const bool has_layer_norm = lstm_params.use_layer_norm(); // Forget gate. + ARM_COMPUTE_RETURN_ERROR_ON(lstm_params.forget_intermediate_scale() == 0); const TensorInfo forget_outstage_info(TensorShape(num_units, batch_size), 1, DataType::QSYMM16, QuantizationInfo(lstm_params.forget_intermediate_scale(), 0)); const TensorInfo mm_out_info(TensorShape(num_units, batch_size), 1, DataType::S32); const float input_to_forget_scale = input_to_forget_weights->quantization_info().uniform().scale * qinput.scale / lstm_params.forget_intermediate_scale(); @@ -707,6 +708,7 @@ Status CLQLSTMLayer::validate(const ITensorInfo *input, ARM_COMPUTE_RETURN_ON_ERROR(CLActivationLayer::validate(&forget_outstage_info, &forget_gate_info, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC))); // Modulation gate. + ARM_COMPUTE_RETURN_ERROR_ON(lstm_params.cell_intermediate_scale() == 0); const TensorInfo cell_outstage_info(TensorShape(num_units, batch_size), 1, DataType::QSYMM16, QuantizationInfo(lstm_params.cell_intermediate_scale(), 0)); const float input_to_cell_scale = input_to_cell_weights->quantization_info().uniform().scale * qinput.scale / lstm_params.cell_intermediate_scale(); ARM_COMPUTE_RETURN_ON_ERROR(validate_mm(gemmlowp_info, input, &input_weights_transposed, &eff_bias_info, input_to_cell_scale, &mm_out_info, &cell_outstage_info)); @@ -742,6 +744,7 @@ Status CLQLSTMLayer::validate(const ITensorInfo *input, ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(forget_gate_bias, lstm_params.input_gate_bias()); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(forget_gate_bias, lstm_params.input_gate_bias()); + ARM_COMPUTE_RETURN_ERROR_ON(lstm_params.input_intermediate_scale() == 0); const TensorInfo input_outstage_info(TensorShape(num_units, batch_size), 1, DataType::QSYMM16, QuantizationInfo(lstm_params.input_intermediate_scale(), 0)); const float input_to_input_scale = lstm_params.input_to_input_weights()->quantization_info().uniform().scale * qinput.scale / lstm_params.input_intermediate_scale(); ARM_COMPUTE_RETURN_ON_ERROR(validate_mm(gemmlowp_info, input, &input_weights_transposed, &eff_bias_info, input_to_input_scale, &mm_out_info, &input_outstage_info)); @@ -780,6 +783,7 @@ Status CLQLSTMLayer::validate(const ITensorInfo *input, quantized_cell_clip))); } // Output gate. + ARM_COMPUTE_RETURN_ERROR_ON(lstm_params.output_intermediate_scale() == 0); const TensorInfo output_outstage_info(TensorShape(num_units, batch_size), 1, DataType::QSYMM16, QuantizationInfo(lstm_params.output_intermediate_scale(), 0)); const float input_to_output_scale = input_to_output_weights->quantization_info().uniform().scale * qinput.scale / lstm_params.output_intermediate_scale(); ARM_COMPUTE_RETURN_ON_ERROR(validate_mm(gemmlowp_info, input, &input_weights_transposed, &eff_bias_info, input_to_output_scale, &mm_out_info, &output_outstage_info)); @@ -815,6 +819,7 @@ Status CLQLSTMLayer::validate(const ITensorInfo *input, const TensorInfo hidden_mul_res(TensorShape(num_units, batch_size), 1, DataType::S32); const TensorInfo hidden_out_info(TensorShape(num_units, batch_size), 1, DataType::QASYMM8_SIGNED); + ARM_COMPUTE_RETURN_ERROR_ON(lstm_params.hidden_state_scale() == 0); ARM_COMPUTE_RETURN_ON_ERROR(CLPixelWiseMultiplicationKernel::validate(&output_gate_info, &input_gate_info, &hidden_mul_res, 1.f, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO)); const float hidden_state_scale = std::pow(2, -15) / lstm_params.hidden_state_scale() * std::pow(2, -15); ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier(hidden_state_scale, &gemmlowp_info.gemmlowp_multiplier, &gemmlowp_info.gemmlowp_shift, /* ignore_epsilon */ true)); @@ -828,6 +833,7 @@ Status CLQLSTMLayer::validate(const ITensorInfo *input, { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(recurrent_to_forget_weights, lstm_params.projection_weights()); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(forget_gate_bias, lstm_params.projection_bias()); + ARM_COMPUTE_RETURN_ERROR_ON(qoutput_state_in.scale == 0); const UniformQuantizationInfo qprojection = lstm_params.projection_weights()->quantization_info().uniform(); const float projection_scale = qprojection.scale * lstm_params.hidden_state_scale() / qoutput_state_in.scale; -- cgit v1.2.1