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-rw-r--r--arm_compute/runtime/CL/functions/CLSoftmaxLayer.h57
-rw-r--r--arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h16
-rw-r--r--arm_compute/runtime/NEON/functions/NESoftmaxLayer.h36
3 files changed, 38 insertions, 71 deletions
diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
index bb01584ff4..fd71f3ed4d 100644
--- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
+++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
@@ -26,8 +26,7 @@
#include "arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h"
#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/functions/CLFlattenLayer.h"
-#include "arm_compute/runtime/CL/functions/CLReshapeLayer.h"
+#include "arm_compute/runtime/CL/functions/CLPermute.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
@@ -47,7 +46,10 @@ class ICLTensor;
* @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f]
*
* This function runs the following kernels:
+ * -# If axis is not 0:
+ * -# @ref CLPermute
* -# @ref CLLogits1DNormKernel
+ * -# @ref CLLogits1DMaxShiftExpSumKernel
*/
template <bool IS_LOG = false>
class CLSoftmaxLayerGeneric : public IFunction
@@ -60,70 +62,47 @@ public:
* @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax
* @param[out] output Destination tensor. Data types supported: same as @p input
* @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f
- * @param[in] axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0.
+ * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
+ * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
*/
- void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t axis = 0);
+ void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f, int32_t axis = 0);
/** Set the input and output tensors.
*
* @param[in] compile_context The compile context to be used.
* @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax
* @param[out] output Destination tensor. Data types supported: same as @p input
* @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f
- * @param[in] axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0.
+ * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
+ * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
*/
- void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t axis = 0);
+ void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, int32_t axis = 0);
/** Static function to check if given info will lead to a valid configuration of @ref CLSoftmaxLayer
*
* @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax
* @param[in] output Destination tensor. Data types supported: same as @p input
* @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f
- * @param[in] axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0.
+ * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
+ * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, size_t axis = 0);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, int32_t axis = 0);
// Inherited methods overridden:
void run() override;
private:
- /** Utility method to configure the kernels needed to flatten the input
- * tensor.
- *
- * @note This function changes the internal state of this class. In particular,
- * it initializes the kernel @p _flatten_kernel and the tensors @p _input_flat and
- * @p _output_flat
- *
- * @param[in] input Original source tensor.
- * @param[in] output Original destination tensor.
- * @param[in] axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0.
- */
- void configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t axis);
- /** Utility method to configure the kernels needed to flatten the input
- * tensor.
- *
- * @note This function changes the internal state of this class. In particular,
- * it initializes the kernel @p _flatten_kernel and the tensors @p _input_flat and
- * @p _output_flat
- *
- * @param[in] compile_context The compile context to be used.
- * @param[in] input Original source tensor.
- * @param[in] output Original destination tensor.
- * @param[in] axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0.
- */
- void configure_reshape_input_kernel(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *output, size_t axis);
-
MemoryGroup _memory_group;
+ CLPermute _permute_input;
+ CLPermute _permute_output;
CLLogits1DMaxShiftExpSumKernel _max_shift_exp_sum_kernel;
CLLogits1DNormKernel _norm_kernel;
- std::unique_ptr<IFunction> _flatten_ptr;
- CLReshapeLayer _reshape;
CLTensor _max;
CLTensor _sum;
CLTensor _tmp;
- CLTensor _input_flattened;
- CLTensor _output_flattened;
- bool _needs_flattening;
+ CLTensor _input_permuted;
+ CLTensor _output_permuted;
+ bool _needs_permute;
};
using CLSoftmaxLayer = CLSoftmaxLayerGeneric<false>;
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h
index 4ccfe2684e..0279edf63d 100644
--- a/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h
+++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h
@@ -50,17 +50,15 @@ public:
GCSoftmaxLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Set the input and output tensors.
*
- * @param[in] input Source tensor. Data types supported: F16/F32
- * @param[out] output Destination tensor. Data types supported: same as @p input
- * @param[in] beta (Optional) A scaling factor for the exponent. Only beta = 1 is supported
- * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
- * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
- * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
- * Must be in range [0, input_num_dimensions).
+ * @param[in] input Source tensor. Data types supported: F16/F32
+ * @param[out] output Destination tensor. Data types supported: same as @p input
+ * @param[in] beta (Optional) A scaling factor for the exponent. Only beta = 1 is supported
+ * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
+ * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
*
- * @note The value of @p reduce_end_axis must be always 0 for GLES
+ * @note The value of @p axis must be always 0 for GLES
*/
- void configure(const IGCTensor *input, IGCTensor *output, float beta = 1.0f, size_t reduce_end_axis = 0);
+ void configure(const IGCTensor *input, IGCTensor *output, float beta = 1.0f, int32_t axis = 0);
// Inherited methods overridden:
void run() override;
diff --git a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h
index 9fb4d85262..20b20201d5 100644
--- a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h
+++ b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h
@@ -28,8 +28,7 @@
#include "arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/MemoryGroup.h"
-#include "arm_compute/runtime/NEON/functions/NEFlattenLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEReshapeLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEPermute.h"
#include "arm_compute/runtime/Tensor.h"
namespace arm_compute
@@ -44,7 +43,9 @@ class ITensor;
* Log Softmax is calculated by :
* @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f]
*
- * This function runs the following kernels:
+ * This function runs the following function/kernels:
+ * -# If axis is not 0:
+ * -# @ref NEPermute
* -# @ref NEFillBorderKernel
* -# @ref NELogits1DMaxKernel
* -# @ref NELogits1DSoftmaxKernel
@@ -70,7 +71,8 @@ public:
* last value of each row to the nearest multiple.
* @param[out] output Destination tensor. Data types supported: same as @p input.
* @param[in] beta (Optional) A scaling factor for the exponent.
- * @param[in] axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0.
+ * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
+ * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
*/
void configure(ITensor *input, ITensor *output, float beta = 1.0f, int32_t axis = 0);
/** Static function to check if given info will lead to a valid configuration of @ref NESoftmaxLayer
@@ -78,7 +80,8 @@ public:
* @param[in] input Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] output Destination tensor info. Data types supported: same as @p input
* @param[in] beta (Optional) A scaling factor for the exponent.
- * @param[in] axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0.
+ * @param[in] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and
+ * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0
*
* @return a status
*/
@@ -88,30 +91,17 @@ public:
void run() override;
private:
- /** Utility method to configure the kernels needed to flatten the input
- * tensor.
- *
- * @note This function changes the internal state of this class. In particular,
- * it initializes the kernel @p _flatten_kernel and the tensors @p _input_flat and
- * @p _output_flat
- *
- * @param[in] input Original source tensor.
- * @param[in] output Original destination tensor.
- * @param[in] axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0.
- */
- void configure_reshape_input_kernel(const ITensor *input, const ITensor *output, int32_t axis);
-
MemoryGroup _memory_group;
+ NEPermute _permute_input;
+ NEPermute _permute_output;
NELogits1DMaxKernel _max_kernel;
NELogits1DSoftmaxKernel<IS_LOG> _softmax_kernel;
- std::unique_ptr<IFunction> _flat_or_reshape_ptr;
NEFillBorderKernel _fill_border_kernel;
- NEReshapeLayer _reshape;
Tensor _max;
Tensor _tmp;
- Tensor _input_flattened;
- Tensor _output_flattened;
- bool _needs_flattening;
+ Tensor _input_permuted;
+ Tensor _output_permuted;
+ bool _needs_permute;
};
using NESoftmaxLayer = NESoftmaxLayerGeneric<false>;
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-13 16:35:12 +0000