COMPMID-3510 [Interface change] Fix definition of "axis" in NESoftmaxLayer and CLSoftmaxLayer
* [Interface change] "axis" argument is renamed to "reduce_end_axis"
* Unify the meaning of "axis"(now "reduce_end_axis") to be the last axis
of the first n dimensions (inclusive)to reduce.
This way the meaning of reduce_end_axis stays the same for both
positive and negative values: it selects a dimension before which all
dimensions (including the selected dimension) are reduced.
Change-Id: I4ab03bd8360b1cd8cac4998df0b1571064a9d4ed
Signed-off-by: SiCong Li <sicong.li@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3278
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/Helpers.h b/arm_compute/core/Helpers.h
index 09c672e..8f1426a 100644
--- a/arm_compute/core/Helpers.h
+++ b/arm_compute/core/Helpers.h
@@ -801,6 +801,19 @@
return x >= 0 ? x % m : (x % m + m) % m;
}
+/** Convert a dimension axis to the number of dimensions in the range [0, @p dim_axis]
+ * Handle negative axis, negative axis is used to specify axis from the end (e.g. -1 for the last axis).
+ *
+ * @param[in] dim_axis The last axis (inclusive) in the range [0, @p dim_axis]
+ * @param[in] num_dims The total number of dimensions
+ *
+ * @return The number of dimensions in the range [0, @p dim_axis]
+ */
+inline size_t dim_index_2_num_dims(int32_t dim_axis, int32_t num_dims)
+{
+ return static_cast<size_t>(wrap_around(dim_axis, num_dims)) + 1;
+}
+
/** Convert negative coordinates to positive in the range [0, num_dims_input]
*
* @param[out] coords Array of coordinates to be converted.
diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
index fadbc43..231a56f 100644
--- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
+++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
@@ -50,6 +50,10 @@
* -# @ref CLLogits1DMaxKernel
* -# @ref CLLogits1DShiftExpSumKernel
* -# @ref CLLogits1DNormKernel
+ * And if the reduce_end_axis is not 0, the function will use one of the the following kernels to reshape the input and
+ * perform softmax on the reshaped input:
+ * -# @ref CLFlattenLayerKernel
+ * -# @ref CLReshapeLayerKernel
*/
template <bool IS_LOG = false>
class CLSoftmaxLayerGeneric : public IFunction
@@ -59,36 +63,39 @@
CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Set the input and output tensors.
*
- * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32
- * @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) Reduction axis. It has the purpose of squashing the first @p axis
- * dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
+ * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32
+ * @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] 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).
*/
- void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t axis = 1);
+ void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t reduce_end_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/F16/F32
* @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) Reduction axis. It has the purpose of squashing the first @p axis
- * dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
+ * @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).
*/
- void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t axis = 1);
+ void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t reduce_end_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/F16/F32
- * @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) Reduction axis. It has the purpose of squashing the first @p axis
- * dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
+ * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32
+ * @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] 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).
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, size_t axis = 1);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, size_t reduce_end_axis = 0);
// Inherited methods overridden:
void run() override;
@@ -101,13 +108,14 @@
* 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) Reduction axis. It has the purpose of squashing the first @p axis
- * dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
+ * @param[in] input Original source tensor.
+ * @param[in] output Original destination tensor.
+ * @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).
*/
- void configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t axis);
+ void configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t reduce_end_axis);
/** Utility method to configure the kernels needed to flatten the input
* tensor.
*
@@ -118,11 +126,12 @@
* @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) Reduction axis. It has the purpose of squashing the first @p axis
- * dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
+ * @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).
*/
- void configure_reshape_input_kernel(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *output, size_t axis);
+ void configure_reshape_input_kernel(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *output, size_t reduce_end_axis);
MemoryGroup _memory_group;
CLLogits1DMaxShiftExpSumKernel _max_shift_exp_sum_kernel;
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h
index 33faae5..e29322c 100644
--- a/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h
+++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -50,16 +50,17 @@
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] axis (Optional) Reduction axis. It has the purpose of squashing the first @p axis
- * dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
+ * @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).
*
- * @note The value of @p axis must be always 1 for GLES
+ * @note The value of @p reduce_end_axis must be always 0 for GLES
*/
- void configure(const IGCTensor *input, IGCTensor *output, float beta = 1.0f, size_t axis = 1);
+ void configure(const IGCTensor *input, IGCTensor *output, float beta = 1.0f, size_t reduce_end_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 b80ceaf..c5c83d8 100644
--- a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h
+++ b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h
@@ -48,6 +48,10 @@
* -# @ref NEFillBorderKernel
* -# @ref NELogits1DMaxKernel
* -# @ref NELogits1DSoftmaxKernel
+ * And if the reduce_end_axis is not 0 or -input_num_dimensions, the function will use one of the the following kernels
+ * to reshape the input and perform softmax on the reshaped input:
+ * -# @ref NEFlattenLayerKernel
+ * -# @ref NEReshapeLayerKernel
*/
template <bool IS_LOG = false>
class NESoftmaxLayerGeneric : public IFunction
@@ -65,30 +69,31 @@
NESoftmaxLayerGeneric &operator=(NESoftmaxLayerGeneric &&) = default;
/** Set the input and output tensors.
*
- * @param[in,out] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. If the width is not a
- * multiple of the internal processing block size, @ref NEFillBorderKernel replicates the
- * 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) Reduction axis. Defaults to -1.
- * Negative index is used to specify axis from the end (e.g. -1 for the last axis).Must be in range [-input_num_dimensions, input_num_dimensions).
- * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
+ * @param[in,out] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. If the width is not a
+ * multiple of the internal processing block size, @ref NEFillBorderKernel replicates the
+ * 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] 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.
+ * Negative index is used to specify axis from the end (e.g. -1 for the last axis).
+ * Must be in range [-input_num_dimensions, input_num_dimensions).
*/
- void configure(ITensor *input, ITensor *output, float beta = 1.0f, int32_t axis = -1);
+ void configure(ITensor *input, ITensor *output, float beta = 1.0f, int32_t reduce_end_axis = 0);
/** Static function to check if given info will lead to a valid configuration of @ref NESoftmaxLayer
*
- * @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) Reduction axis. Defaults to -1.
- * Negative index is used to specify axis from the end (e.g. -1 for the last axis).Must be in range [-input_num_dimensions, input_num_dimensions).
- * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
- *
+ * @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] 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.
+ * Negative index is used to specify axis from the end (e.g. -1 for the last axis).
+ * Must be in range [-input_num_dimensions, input_num_dimensions).
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, int32_t axis = -1);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, int32_t reduce_end_axis = 0);
// Inherited methods overridden:
void run() override;
@@ -101,14 +106,15 @@
* 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) Reduction axis. Defaults to -1.
- * Negative index is used to specify axis from the end (e.g. -1 for the last axis).Must be in range [-input_num_dimensions, input_num_dimensions).
- * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image,
- * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.
+ * @param[in] input Original source tensor.
+ * @param[in] output Original destination tensor.
+ * @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.
+ * Negative index is used to specify axis from the end (e.g. -1 for the last axis).
+ * Must be in range [-input_num_dimensions, input_num_dimensions).
*/
- void configure_reshape_input_kernel(const ITensor *input, const ITensor *output, int32_t axis);
+ void configure_reshape_input_kernel(const ITensor *input, const ITensor *output, int32_t reduce_end_axis);
MemoryGroup _memory_group;
NELogits1DMaxKernel _max_kernel;