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path: root/src/core/cpu/kernels/CpuSoftmaxKernel.cpp
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Diffstat (limited to 'src/core/cpu/kernels/CpuSoftmaxKernel.cpp')
-rw-r--r--src/core/cpu/kernels/CpuSoftmaxKernel.cpp84
1 files changed, 37 insertions, 47 deletions
diff --git a/src/core/cpu/kernels/CpuSoftmaxKernel.cpp b/src/core/cpu/kernels/CpuSoftmaxKernel.cpp
index 1e00e12050..c562699092 100644
--- a/src/core/cpu/kernels/CpuSoftmaxKernel.cpp
+++ b/src/core/cpu/kernels/CpuSoftmaxKernel.cpp
@@ -72,12 +72,12 @@ static const SoftmaxLogits1DKernel available_logits_1d_kernels[] =
{
#if defined(ARM_COMPUTE_ENABLE_SVE)
{
- "sve_softmax_logits_1d_float",
+ "sve_fp32_softmax_logits_1d",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::F32) && data.ci.has_sve(); },
REGISTER_FP32_SVE(arm_compute::cpu::sve_softmax_logits_1d_float<float>)
},
{
- "sve_softmax_logits_1d_float",
+ "sve_fp16_softmax_logits_1d",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::F16) && data.ci.has_sve(); },
REGISTER_FP16_SVE(arm_compute::cpu::sve_softmax_logits_1d_float<float16_t>)
},
@@ -85,13 +85,13 @@ static const SoftmaxLogits1DKernel available_logits_1d_kernels[] =
#if defined(ARM_COMPUTE_ENABLE_NEON)
{
- "neon_softmax_logits_1d_float",
+ "neon_fp32_softmax_logits_1d",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::F32); },
REGISTER_FP32_NEON(arm_compute::cpu::neon_softmax_logits_1d_float<float>)
},
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
{
- "neon_softmax_logits_1d_float",
+ "neon_fp16_softmax_logits_1d",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::F16); },
REGISTER_FP16_NEON(arm_compute::cpu::neon_softmax_logits_1d_float<float16_t>)
},
@@ -100,23 +100,23 @@ static const SoftmaxLogits1DKernel available_logits_1d_kernels[] =
#if defined(ARM_COMPUTE_ENABLE_SVE2)
{
- "sve_softmax_logits_1d_quantized",
+ "sve2_qu8_softmax_logits_1d",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::QASYMM8) && data.ci.has_sve2(); },
REGISTER_QASYMM8_SVE(arm_compute::cpu::sve_softmax_logits_1d_quantized<qasymm8_t>)
},
{
- "sve_softmax_logits_1d_quantized",
+ "sve2_qs8_softmax_logits_1d",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED) && data.ci.has_sve2(); },
REGISTER_QASYMM8_SIGNED_SVE(arm_compute::cpu::sve_softmax_logits_1d_quantized<qasymm8_signed_t>)
},
#endif /* defined(ARM_COMPUTE_ENABLE_SVE2) */
{
- "neon_softmax_logits_1d_quantized",
+ "neon_qu8_softmax_logits_1d",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::QASYMM8); },
REGISTER_QASYMM8_NEON(arm_compute::cpu::neon_softmax_logits_1d_quantized<qasymm8_t>)
},
{
- "neon_softmax_logits_1d_quantized",
+ "neon_qs8_softmax_logits_1d",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); },
REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::neon_softmax_logits_1d_quantized<qasymm8_signed_t>)
},
@@ -126,46 +126,46 @@ static const SoftmaxLogits1DMaxKernel available_logits_1d_max_kernels[] =
{
#if defined(ARM_COMPUTE_ENABLE_SVE)
{
- "sve_logits_1d_max",
+ "sve_fp32_logits_1d_max",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::F32) && data.ci.has_sve(); },
REGISTER_FP32_SVE(arm_compute::cpu::sve_logits_1d_max<float>)
},
{
- "sve_logits_1d_max",
+ "sve_fp16_logits_1d_max",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::F16) && data.ci.has_sve(); },
REGISTER_FP16_SVE(arm_compute::cpu::sve_logits_1d_max<float16_t>)
},
{
- "sve_logits_1d_max",
+ "sve_qu8_logits_1d_max",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::QASYMM8) && data.ci.has_sve(); },
REGISTER_QASYMM8_SVE(arm_compute::cpu::sve_logits_1d_max<qasymm8_t>)
},
{
- "sve_logits_1d_max",
+ "sve_qs8_logits_1d_max",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED) && data.ci.has_sve(); },
REGISTER_QASYMM8_SIGNED_SVE(arm_compute::cpu::sve_logits_1d_max<qasymm8_signed_t>)
},
#endif /* defined(ARM_COMPUTE_ENABLE_SVE) */
#if defined(ARM_COMPUTE_ENABLE_NEON)
{
- "neon_logits_1d_max",
+ "neon_fp32_logits_1d_max",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::F32); },
REGISTER_FP32_NEON(arm_compute::cpu::neon_logits_1d_max<float>)
},
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
{
- "neon_logits_1d_max",
+ "neon_fp16_logits_1d_max",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::F16); },
REGISTER_FP16_NEON(arm_compute::cpu::neon_logits_1d_max<float16_t>)
},
#endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) */
{
- "neon_logits_1d_max",
+ "neon_qu8_logits_1d_max",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::QASYMM8); },
REGISTER_QASYMM8_NEON(arm_compute::cpu::neon_logits_1d_max<qasymm8_t>)
},
{
- "neon_logits_1d_max",
+ "neon_qs8_logits_1d_max",
[](const SoftmaxSelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); },
REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::neon_logits_1d_max<qasymm8_signed_t>)
},
@@ -214,15 +214,9 @@ Status validate_arguments_logits_1d_max(const ITensorInfo &input, const ITensorI
} // namespace
-CpuLogits1DMaxKernel::CpuLogits1DMaxKernel()
-{
-}
-
void CpuLogits1DMaxKernel::configure(const ITensorInfo *src, ITensorInfo *dst)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
-
- // Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_1d_max(*src, *dst));
// Softmax across the x dimension
@@ -230,8 +224,13 @@ void CpuLogits1DMaxKernel::configure(const ITensorInfo *src, ITensorInfo *dst)
// Output auto initialization if not yet initialized
auto_init_if_empty(*dst, output_shape, 1, src->data_type(), src->quantization_info());
- Window win = calculate_max_window(*src, Steps());
+ const auto *uk = get_implementation_logits_max(SoftmaxSelectorData{ src->data_type(), CPUInfo::get() });
+ ARM_COMPUTE_ERROR_ON_NULLPTR(uk);
+
+ _run_method = uk->ukernel;
+ _name = std::string("CpuLogits1DMaxKernel").append("/").append(uk->name);
+ Window win = calculate_max_window(*src, Steps());
ICpuKernel::configure(win);
}
@@ -248,17 +247,17 @@ void CpuLogits1DMaxKernel::run_op(ITensorPack &tensors, const Window &window, co
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
+ ARM_COMPUTE_ERROR_ON(_run_method == nullptr);
const auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
auto dst = tensors.get_tensor(TensorType::ACL_DST);
- const auto *uk = get_implementation_logits_max(SoftmaxSelectorData{ src->info()->data_type(), CPUInfo::get() });
- uk->ukernel(src, dst, window);
+ _run_method(src, dst, window);
}
const char *CpuLogits1DMaxKernel::name() const
{
- return "CpuLogits1DMaxKernel";
+ return _name.c_str();
}
namespace
@@ -302,21 +301,11 @@ Status validate_arguments_logits_softmax(const ITensorInfo &src, const ITensorIn
} // namespace
template <bool IS_LOG>
-CpuLogits1DSoftmaxKernel<IS_LOG>::CpuLogits1DSoftmaxKernel()
- : _beta(1.0f)
-{
-}
-
-template <bool IS_LOG>
void CpuLogits1DSoftmaxKernel<IS_LOG>::configure(const ITensorInfo *src, const ITensorInfo *max, ITensorInfo *dst, const float beta, ITensorInfo *tmp)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src, max, dst, tmp);
- ARM_COMPUTE_ERROR_ON_NULLPTR(src, max, dst, tmp);
- // Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_softmax(*src, *max, *dst, beta, *tmp, IS_LOG));
- _beta = beta;
-
// Configure kernel window
const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(src->data_type());
@@ -328,6 +317,15 @@ void CpuLogits1DSoftmaxKernel<IS_LOG>::configure(const ITensorInfo *src, const I
const DataType tmp_data_type = is_quantized_asymmetric ? DataType::F32 : src->data_type();
auto_init_if_empty(*tmp, TensorInfo(*src).set_data_type(tmp_data_type).reset_padding());
+ const auto *uk = get_implementation_logits(SoftmaxSelectorData{ src->data_type(), CPUInfo::get() });
+ ARM_COMPUTE_ERROR_ON_NULLPTR(uk);
+
+ std::string kernel_name = IS_LOG ? std::string("CpuLogits1DLogSoftmaxKernel") : std::string("CpuLogits1DSoftmaxKernel");
+
+ _beta = beta;
+ _run_method = uk->ukernel;
+ _name = kernel_name.append("/").append(uk->name);
+
// Configure kernel window
Window win = calculate_max_window(*max, Steps());
@@ -350,6 +348,7 @@ void CpuLogits1DSoftmaxKernel<IS_LOG>::run_op(ITensorPack &tensors, const Window
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
+ ARM_COMPUTE_ERROR_ON(_run_method == nullptr);
const auto src = tensors.get_const_tensor(TensorType::ACL_SRC_0);
auto max = tensors.get_tensor(TensorType::ACL_SRC_1);
@@ -362,22 +361,13 @@ void CpuLogits1DSoftmaxKernel<IS_LOG>::run_op(ITensorPack &tensors, const Window
ARM_COMPUTE_ERROR_ON(tmp->info()->total_size() < (info.num_threads * tmp_size_for_thread));
void *tmp_for_thread = tmp->buffer() + (info.thread_id * tmp_size_for_thread);
-
- const auto *uk = get_implementation_logits(SoftmaxSelectorData{ src->info()->data_type(), CPUInfo::get() });
- uk->ukernel(src, max, tmp_for_thread, dst, _beta, IS_LOG, window);
+ _run_method(src, max, tmp_for_thread, dst, _beta, IS_LOG, window);
}
template <bool IS_LOG>
const char *CpuLogits1DSoftmaxKernel<IS_LOG>::name() const
{
- if(IS_LOG)
- {
- return "CpuLogits1DSoftmaxKernel";
- }
- else
- {
- return "CpuLogits1DLogSoftmaxKernel";
- }
+ return _name.c_str();
}
template class CpuLogits1DSoftmaxKernel<true>;
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-29 00:07:10 +0000