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Diffstat (limited to 'src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp')
-rw-r--r--src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp55
1 files changed, 37 insertions, 18 deletions
diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
index 4c602b3640..5133756993 100644
--- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
@@ -51,7 +51,8 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor
ITensor *output,
const PadStrideInfo &conv_info,
unsigned int depth_multiplier,
- const ActivationLayerInfo &act_info)
+ const ActivationLayerInfo &act_info,
+ const Size2D &dilation)
{
ARM_COMPUTE_UNUSED(act_info);
@@ -87,8 +88,8 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor
_permute_weights.configure(weights, &_permuted_weights, PermutationVector(1U, 2U, 0U));
_permuted_weights.info()->set_data_layout(DataLayout::NCHW);
- // Configure optimized depthwise
- _dwc_kernel.configure(&_permuted_input, &_permuted_weights, (_is_quantized) ? &_accumulator : &_permuted_output, conv_info, depth_multiplier);
+ // Configure depthwise
+ _dwc_kernel.configure(&_permuted_input, &_permuted_weights, (_is_quantized) ? &_accumulator : &_permuted_output, conv_info, depth_multiplier, dilation);
// Configure border handler
_border_handler.configure(&_permuted_input, _dwc_kernel.border_size(), BorderMode::CONSTANT, zero_value);
@@ -99,7 +100,7 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor
else
{
// Configure depthwise convolution kernel
- _dwc_kernel.configure(input, weights, (_is_quantized) ? &_accumulator : output, conv_info, depth_multiplier);
+ _dwc_kernel.configure(input, weights, (_is_quantized) ? &_accumulator : output, conv_info, depth_multiplier, dilation);
// Configure border handler
_border_handler.configure(input, _dwc_kernel.border_size(), BorderMode::CONSTANT, zero_value);
@@ -185,18 +186,25 @@ void NEDepthwiseConvolutionLayer3x3::configure(ITensor *input,
const ActivationLayerInfo &act_info,
const Size2D &dilation)
{
- ARM_COMPUTE_ERROR_ON(dilation.x() != 1 || dilation.y() != 1);
- ARM_COMPUTE_UNUSED(dilation);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
+ // idx_w and idx_h only used for validation
+ const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH);
+ const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT);
+ ARM_COMPUTE_UNUSED(idx_w);
+ ARM_COMPUTE_UNUSED(idx_h);
+
+ ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_w) + (weights->info()->dimension(idx_w) - 1) * (dilation.x() - 1) > input->info()->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right());
+ ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_h) + (weights->info()->dimension(idx_h) - 1) * (dilation.y() - 1) > input->info()->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom());
+
_original_weights = weights;
_is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type());
_has_bias = biases != nullptr;
_is_optimized = NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input->info(),
weights->info(),
conv_info,
- depth_multiplier);
+ depth_multiplier, dilation);
_is_nchw = input->info()->data_layout() == DataLayout::NCHW;
_permute = _is_optimized == _is_nchw;
_is_prepared = false;
@@ -209,7 +217,7 @@ void NEDepthwiseConvolutionLayer3x3::configure(ITensor *input,
}
else
{
- configure_generic(input, weights, biases, output, conv_info, depth_multiplier, act_info);
+ configure_generic(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation);
}
// Configure activation
@@ -230,7 +238,11 @@ Status NEDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::UNKNOWN);
- ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() != 1 || dilation.y() != 1);
+ ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() < 1 || dilation.y() < 1);
+ const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH);
+ const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT);
+ ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) + (weights->dimension(idx_w) - 1) * (dilation.x() - 1) > input->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right());
+ ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_h) + (weights->dimension(idx_h) - 1) * (dilation.y() - 1) > input->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom());
if(biases != nullptr)
{
@@ -239,7 +251,7 @@ Status NEDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input
ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(channel_idx));
}
- if(!NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input, weights, conv_info, depth_multiplier))
+ if(!NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input, weights, conv_info, depth_multiplier, dilation))
{
const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type());
TensorInfo accumulator = TensorInfo(output->clone()->set_is_resizable(true).reset_padding().set_data_type(DataType::S32));
@@ -356,12 +368,17 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh
{
const unsigned int channel_idx = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::CHANNEL);
ARM_COMPUTE_UNUSED(channel_idx);
- ARM_COMPUTE_ERROR_ON(dilation.x() != 1 || dilation.y() != 1);
- ARM_COMPUTE_UNUSED(dilation);
-
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
ARM_COMPUTE_ERROR_ON((input->info()->dimension(channel_idx) * depth_multiplier) != weights->info()->dimension(channel_idx));
+ // idx_w and idx_h only used for validation
+ const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH);
+ const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT);
+ ARM_COMPUTE_UNUSED(idx_w);
+ ARM_COMPUTE_UNUSED(idx_h);
+
+ ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_w) + (weights->info()->dimension(idx_w) - 1) * (dilation.x() - 1) > input->info()->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right());
+ ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_h) + (weights->info()->dimension(idx_h) - 1) * (dilation.y() - 1) > input->info()->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom());
_is_nhwc = input->info()->data_layout() == DataLayout::NHWC;
@@ -392,7 +409,7 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh
bool append_bias = (biases != nullptr) && !_is_quantized;
// Calculate output shape
- TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input->info(), *weights->info(), conv_info, depth_multiplier);
+ TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input->info(), *weights->info(), conv_info, depth_multiplier, dilation);
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
@@ -420,7 +437,7 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh
shape_im2col.set(1, conv_size);
shape_im2col.set(2, weights_z);
_input_reshaped.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_im2col).set_data_layout(DataLayout::NCHW));
- _im2col_kernel.configure(input_to_use, &_input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier);
+ _im2col_kernel.configure(input_to_use, &_input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier, dilation);
// Weights reshape configuration
const TensorShape shape_weights_reshape(patch_size, weights_z);
@@ -491,11 +508,13 @@ Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::UNKNOWN);
- ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() != 1 || dilation.y() != 1);
+ ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() < 1 || dilation.y() < 1);
const unsigned int width_idx = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH);
const unsigned int height_idx = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT);
+ ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(width_idx) + (weights->dimension(width_idx) - 1) * (dilation.x() - 1) > input->dimension(width_idx) + conv_info.pad_left() + conv_info.pad_right());
+ ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(height_idx) + (weights->dimension(height_idx) - 1) * (dilation.y() - 1) > input->dimension(height_idx) + conv_info.pad_top() + conv_info.pad_bottom());
// Clone output to use auto init
auto output_clone = output->clone();
@@ -522,7 +541,7 @@ Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe
const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type());
const bool append_bias = (biases != nullptr) && !is_quantized;
- TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier);
+ TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
const size_t weights_w = weights_to_use->dimension(0);
const size_t weights_h = weights_to_use->dimension(1);
const size_t weights_z = weights_to_use->dimension(2);
@@ -549,7 +568,7 @@ Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe
shape_im2col.set(1, conv_size);
shape_im2col.set(2, weights_z);
TensorInfo input_reshaped(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_im2col).set_data_layout(DataLayout::NCHW));
- ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseIm2ColKernel::validate(input_to_use, &input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier));
+ ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseIm2ColKernel::validate(input_to_use, &input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier, dilation));
// Weights reshape configuration
const TensorShape shape_weights_reshape(patch_size, weights_z);
generated by cgit v1.2.1 (git 2.23.0) at 2024-04-29 01:14:18 +0000