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-rw-r--r--arm_compute/core/Types.h20
-rw-r--r--arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h34
-rw-r--r--arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h1
-rw-r--r--src/runtime/CL/functions/CLFullyConnectedLayer.cpp12
-rw-r--r--src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp25
5 files changed, 58 insertions, 34 deletions
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index 46e6dba1a0..639170f0fd 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -946,18 +946,19 @@ class WeightsInfo
public:
/** Default constructor */
WeightsInfo()
- : _are_reshaped(false), _kernel_width(0), _kernel_height(0), _num_kernels(0)
+ : _are_reshaped(false), _kernel_width(0), _kernel_height(0), _num_kernels(0), _retain_internal_weights(false)
{
}
/** Constructor
*
- * @param[in] are_reshaped True if the weights have been reshaped
- * @param[in] kernel_width Kernel width.
- * @param[in] kernel_height Kernel height.
- * @param[in] num_kernels Number of convolution kernels.
+ * @param[in] are_reshaped True if the weights have been reshaped
+ * @param[in] kernel_width Kernel width.
+ * @param[in] kernel_height Kernel height.
+ * @param[in] num_kernels Number of convolution kernels.
+ * @param[in] retain_internal_weights (Optional) True if internal reshaped weights must be retained. Used for reconfiguration purposes. Default is false.
*/
- WeightsInfo(bool are_reshaped, unsigned int kernel_width, unsigned int kernel_height, unsigned int num_kernels)
- : _are_reshaped(are_reshaped), _kernel_width(kernel_width), _kernel_height(kernel_height), _num_kernels(num_kernels)
+ WeightsInfo(bool are_reshaped, unsigned int kernel_width, unsigned int kernel_height, unsigned int num_kernels, bool retain_internal_weights = false)
+ : _are_reshaped(are_reshaped), _kernel_width(kernel_width), _kernel_height(kernel_height), _num_kernels(num_kernels), _retain_internal_weights(retain_internal_weights)
{
}
/** Flag which specifies if the weights tensor has been reshaped.
@@ -984,12 +985,17 @@ public:
{
return std::make_pair(_kernel_width, _kernel_height);
}
+ bool retain_internal_weights() const
+ {
+ return _retain_internal_weights;
+ }
private:
const bool _are_reshaped;
const unsigned int _kernel_width;
const unsigned int _kernel_height;
const unsigned int _num_kernels;
+ const bool _retain_internal_weights;
};
/** GEMM reshape information class. This class stores the necessary information about matrix A and matrix B reshape.
diff --git a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
index 7fb5af9229..127d8acf10 100644
--- a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
+++ b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
@@ -86,26 +86,32 @@ public:
CLFullyConnectedLayer &operator=(CLFullyConnectedLayer &&) = default;
/** Set the input and output tensors.
*
- * @param[in] input Source tensor. Data type supported: QS8/QASYMM8/QS16/F16/F32.
- * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input
- * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input.
- * @param[out] output Destination tensor. Data type supported: Same as @p input.
- * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true.
- * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false.
+ * @param[in] input Source tensor. Data type supported: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input
+ * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input.
+ * @param[out] output Destination tensor. Data type supported: Same as @p input.
+ * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true.
+ * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false.
+ * @param[in] retain_internal_weights (Optional) Retain internal reshaped weights. Defaults to false.
+ * Used for reconfiguration purposes.
*/
- void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose_weights = true, bool are_weights_reshaped = false);
+ void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose_weights = true, bool are_weights_reshaped = false,
+ bool retain_internal_weights = false);
/** Static function to check if given info will lead to a valid configuration of @ref CLFullyConnectedLayer
*
- * @param[in] input Source tensor. Data type supported: QS8/QASYMM8/QS16/F16/F32.
- * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input
- * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input.
- * @param[in] output Destination tensor. Data type supported: Same as @p input.
- * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true.
- * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false.
+ * @param[in] input Source tensor. Data type supported: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input
+ * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input.
+ * @param[in] output Destination tensor. Data type supported: Same as @p input.
+ * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true.
+ * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false.
+ * @param[in] retain_internal_weights (Optional) Retain internal reshaped weights. Defaults to false.
+ * Used for reconfiguration purposes.
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, bool transpose_weights = true, bool are_weights_reshaped = false);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, bool transpose_weights = true, bool are_weights_reshaped = false,
+ bool retain_internal_weights = false);
//Inherited methods override
void run() override;
diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
index 3dde52989b..aaa432616d 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
@@ -195,6 +195,7 @@ private:
bool _is_quantized;
bool _is_activationlayer_enabled;
bool _is_prepared;
+ bool _retain_internal_weights;
};
}
#endif /* __ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H__ */
diff --git a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
index 151fa1b5fa..44bf28374f 100644
--- a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
+++ b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
@@ -133,7 +133,8 @@ void CLFullyConnectedLayer::configure_fc_fc(const ICLTensor *input, const ICLTen
configure_mm(input, weights, output);
}
-void CLFullyConnectedLayer::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose_weights, bool are_weights_reshaped)
+void CLFullyConnectedLayer::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose_weights, bool are_weights_reshaped,
+ bool retain_internal_weights)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
@@ -143,7 +144,8 @@ void CLFullyConnectedLayer::configure(const ICLTensor *input, const ICLTensor *w
biases != nullptr ? biases->info() : nullptr,
output->info(),
transpose_weights,
- are_weights_reshaped));
+ are_weights_reshaped,
+ retain_internal_weights));
_are_weights_reshaped = transpose_weights ? are_weights_reshaped : true;
_is_fc_after_conv = true;
@@ -220,10 +222,14 @@ void CLFullyConnectedLayer::configure(const ICLTensor *input, const ICLTensor *w
_gemmlowp_output_stage.configure(&_gemmlowp_output, biases, output, output_multiplier, output_shift, output->info()->quantization_info().offset);
_gemmlowp_output.allocator()->allocate();
}
+
+ _are_weights_reshaped = _are_weights_reshaped || retain_internal_weights;
}
-Status CLFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, bool transpose_weights, bool are_weights_reshaped)
+Status CLFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, bool transpose_weights, bool are_weights_reshaped,
+ bool retain_internal_weights)
{
+ ARM_COMPUTE_UNUSED(retain_internal_weights);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, output);
diff --git a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
index 610eec4d67..4f87043373 100644
--- a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
@@ -91,7 +91,8 @@ void CLConvolutionLayerReshapeWeights::run()
CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(memory_manager), _reshape_weights(), _im2col_kernel(), _mm_gemm(memory_manager), _mm_gemmlowp(memory_manager), _gemmlowp_output_stage(), _col2im_kernel(), _activationlayer_function(),
- _original_weights(nullptr), _im2col_output(), _weights_reshaped(), _gemm_output(), _tmp_output(), _is_quantized(false), _is_activationlayer_enabled(false), _is_prepared(false)
+ _original_weights(nullptr), _im2col_output(), _weights_reshaped(), _gemm_output(), _tmp_output(), _is_quantized(false), _is_activationlayer_enabled(false), _is_prepared(false),
+ _retain_internal_weights(false)
{
}
@@ -165,9 +166,10 @@ void CLGEMMConvolutionLayer::configure(const ICLTensor *input, const ICLTensor *
dilation,
act_info));
- _is_prepared = false;
- _original_weights = weights;
- _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type());
+ _is_prepared = false;
+ _original_weights = weights;
+ _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type());
+ _retain_internal_weights = weights_info.retain_internal_weights();
const DataType dt = input->info()->data_type();
@@ -404,17 +406,20 @@ void CLGEMMConvolutionLayer::prepare()
{
if(!_is_prepared)
{
- // Run weights reshaping and mark as unused
- ARM_COMPUTE_ERROR_ON(!_original_weights->is_used());
- _weights_reshaped.allocator()->allocate();
- _reshape_weights.run();
- _original_weights->mark_as_unused();
+ if(!_retain_internal_weights)
+ {
+ // Run weights reshaping and mark as unused
+ ARM_COMPUTE_ERROR_ON(!_original_weights->is_used());
+ _weights_reshaped.allocator()->allocate();
+ _reshape_weights.run();
+ _original_weights->mark_as_unused();
+ }
// Run GEMM prepare
if(!_is_quantized)
{
_mm_gemm.prepare();
- if(!_weights_reshaped.is_used())
+ if(!_weights_reshaped.is_used() && !_retain_internal_weights)
{
_weights_reshaped.allocator()->free();
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-20 19:52:00 +0000