COMPMID-1783: NEGEMMConvolutionLayer fails for QASYMM8 on 32bit
Change-Id: Ibc8d903c8d3c97b51dc8a3344197b56ad9d6c00e
diff --git a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
index 2433201..0232a83 100644
--- a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
@@ -91,8 +91,8 @@
NEGEMMConvolutionLayer::NEGEMMConvolutionLayer(const std::shared_ptr<IMemoryManager> &memory_manager)
: _memory_group(memory_manager), _reshape_weights(), _im2col_kernel(), _mm_gemm(), _mm_gemmlowp(memory_manager), _gemmlowp_output_stage(), _col2im_kernel(), _activationlayer_function(),
- _add_bias_kernel(), _original_weights(nullptr), _im2col_output(), _weights_reshaped(), _gemm_output(), _tmp_output(), _data_layout(DataLayout::NCHW), _append_bias(false), _skip_im2col(false),
- _skip_col2im(false), _is_quantized(false), _is_activationlayer_enabled(false), _is_prepared(false)
+ _add_bias_kernel(), _reshape_layer(), _original_weights(nullptr), _im2col_output(), _weights_reshaped(), _gemm_output(), _tmp_output(), _data_layout(DataLayout::NCHW), _append_bias(false),
+ _skip_im2col(false), _skip_col2im(false), _is_quantized(false), _is_activationlayer_enabled(false), _is_prepared(false)
{
}
@@ -199,7 +199,6 @@
_is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type());
_data_layout = data_layout;
_skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1);
- _skip_col2im = data_layout == DataLayout::NHWC;
_append_bias = (biases != nullptr) && (!_is_quantized);
_is_activationlayer_enabled = act_info.enabled();
@@ -218,15 +217,19 @@
dilation);
// Check if GEMM3D is supported
- if(_skip_col2im)
+ if(data_layout == DataLayout::NHWC)
{
+ _skip_col2im = bool(validate_gemm3d(input->info()->data_type(), conv_h, true));
// If not supported, we need to perform im2col and col2im (or reshape layer)
- if(!bool(validate_gemm3d(input->info()->data_type(), conv_h, _skip_im2col)))
+ if(!_skip_col2im)
{
_skip_im2col = false;
- _skip_col2im = false;
}
}
+ else
+ {
+ _skip_col2im = false;
+ }
const ITensor *biases_to_use = (_append_bias && !_skip_im2col) ? biases : nullptr;
@@ -300,7 +303,6 @@
// Configure output stage for quantized case
if(_is_quantized)
{
- const bool skip_reshape = data_layout == DataLayout::NHWC;
const QuantizationInfo input_quant_info = input->info()->quantization_info();
const QuantizationInfo output_quant_info = (output->info()->total_size() == 0) ? input_quant_info : output->info()->quantization_info();
@@ -308,7 +310,7 @@
int output_multiplier, output_shift;
quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
- if(!skip_reshape)
+ if(!_skip_col2im)
{
_memory_group.manage(&_tmp_output);
gemm_output_staged_to_use = &_tmp_output;
@@ -336,13 +338,21 @@
_gemmlowp_output_stage.configure(gemm_output_to_use, biases, gemm_output_staged_to_use, output_multiplier, output_shift, output_quant_info.offset, min_activation, max_activation);
}
- if(!_skip_col2im && _data_layout == DataLayout::NCHW)
+ if(!_skip_col2im)
{
- // Configure col2im
- _col2im_kernel.configure(_is_quantized ? gemm_output_staged_to_use : gemm_output_to_use, output, Size2D(conv_w, conv_h));
+ if(_data_layout == DataLayout::NCHW)
+ {
+ // Configure col2im
+ _col2im_kernel.configure(_is_quantized ? gemm_output_staged_to_use : gemm_output_to_use, output, Size2D(conv_w, conv_h));
+ }
+ else
+ {
+ // Configure reshape layer
+ _reshape_layer.configure(_is_quantized ? gemm_output_staged_to_use : gemm_output_to_use, output);
+ }
}
- if(_is_quantized && data_layout == DataLayout::NCHW)
+ if(_is_quantized && !_skip_col2im)
{
_tmp_output.allocator()->allocate();
}
@@ -393,7 +403,6 @@
const bool is_quantized = is_data_type_quantized_asymmetric(data_type);
const bool append_bias = (biases != nullptr) && (!is_quantized);
bool skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1);
- bool skip_col2im = data_layout == DataLayout::NHWC;
bool is_activation_enabled = act_info.enabled();
// Get convolved dimensions
@@ -408,6 +417,17 @@
dilation);
// Check if GEMM3D is supported
+ bool skip_col2im = false;
+ if(data_layout == DataLayout::NHWC)
+ {
+ skip_col2im = bool(validate_gemm3d(input->data_type(), conv_h, true));
+ // If not supported, we need to perform im2col and col2im (or reshape layer)
+ if(!skip_col2im)
+ {
+ skip_im2col = false;
+ }
+ }
+
if(skip_col2im)
{
// If not supported, we need to perform im2col and col2im (or reshape layer)
@@ -494,17 +514,16 @@
if(is_quantized)
{
- const bool skip_reshape = data_layout == DataLayout::NHWC;
const QuantizationInfo input_quant_info = input->quantization_info();
const QuantizationInfo output_quant_info = (output->total_size() == 0) ? input_quant_info : output->quantization_info();
const float multiplier = input_quant_info.scale * weights_to_use->quantization_info().scale / output_quant_info.scale;
int output_multiplier, output_shift;
quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
- if(!skip_reshape)
+ if(!skip_col2im)
{
tmp_info = TensorInfo(gemm_output_to_use->tensor_shape(), 1, DataType::QASYMM8);
- tmp_info.set_quantization_info(output->quantization_info());
+ tmp_info.set_quantization_info(output->quantization_info()).set_data_layout(data_layout);
gemm_output_staged_to_use = &tmp_info;
}
@@ -583,9 +602,16 @@
}
// Reshape output matrix
- if(!_skip_col2im && _data_layout == DataLayout::NCHW)
+ if(!_skip_col2im)
{
- NEScheduler::get().schedule(&_col2im_kernel, Window::DimY);
+ if(_data_layout == DataLayout::NCHW)
+ {
+ NEScheduler::get().schedule(&_col2im_kernel, Window::DimY);
+ }
+ else
+ {
+ _reshape_layer.run();
+ }
}
if(_is_activationlayer_enabled)