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author | Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> | 2024-04-29 22:53:58 +0100 |
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committer | Suhail M <MohammedSuhail.Munshi@arm.com> | 2024-05-08 12:07:31 +0000 |
commit | 2fea13593a4753316ae488edf489cb4b00150153 (patch) | |
tree | 423e6369a74c44b505dd8fd4d62bde0946ec2e32 /src/gpu | |
parent | c22e1263ba3a6945ceb1fdccb33eac512fd156fb (diff) | |
download | ComputeLibrary-2fea13593a4753316ae488edf489cb4b00150153.tar.gz |
Add batched indices support to Scatter GPU Implementation
Resolves: [COMPMID-6897]
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Change-Id: I70b1c3c5f0de8484fcb6c3b0cc0d0d8c059b0f58
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11525
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/gpu')
-rw-r--r-- | src/gpu/cl/kernels/ClScatterKernel.cpp | 44 |
1 files changed, 34 insertions, 10 deletions
diff --git a/src/gpu/cl/kernels/ClScatterKernel.cpp b/src/gpu/cl/kernels/ClScatterKernel.cpp index 21c0253f91..f76a674b27 100644 --- a/src/gpu/cl/kernels/ClScatterKernel.cpp +++ b/src/gpu/cl/kernels/ClScatterKernel.cpp @@ -66,6 +66,7 @@ Status ClScatterKernel::validate(const ITensorInfo *updates, const int32_t upt_dims = upt_shape.num_dimensions(); const int32_t dst_dims = dst_shape.num_dimensions(); const int32_t ind_dims = ind_shape.num_dimensions(); + const int32_t data_dim = upt_dims - (ind_dims - 1); // Number of batch dims is the number of indices dims - 1 const int32_t index_len = ind_shape[0]; @@ -73,14 +74,34 @@ Status ClScatterKernel::validate(const ITensorInfo *updates, ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(indices, DataType::S32); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(dst, DataType::F32, DataType::F16, DataType::S32, DataType::S16, DataType::S8, DataType::U32, DataType::U16, DataType::U8); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(ind_dims > 2, "Only 2D indices tensors are currently supported."); + + // Check data dims in update tensor and output tensor are equal + for (int32_t i = 0; i < data_dim; i++) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(upt_shape[i] != dst_shape[i], + "Data dims should be same size in both updates and ouput tensor."); + } + + // Check if batch dims in indices and updates tensor are equal. + for (int32_t i = 0; i < ind_dims - 1; i++) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(upt_shape[data_dim + i] != ind_shape[i + 1], + "Batch dimensions should be the same in updates and indices tensor."); + } + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(ind_shape[1] != upt_shape[data_dim], + "Height of indices tensor should match size of highest dimension in updates tensor " + "(Excluding batch dimension)"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG( - ind_shape[1] != upt_shape[upt_dims - 1], - "Height of indices tensor should match size of highest dimension in updates tensor."); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(upt_dims > dst_dims, "Update tensor cannot have more dims than output tensor."); + data_dim >= dst_dims, "Update tensor cannot have more dims than output tensor. (Excluding batch dimensions)"); + ARM_COMPUTE_RETURN_ERROR_ON(index_len != dst_dims - data_dim); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((ind_dims < 2), "Shape of Indices tensor must be at least 2D"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(index_len > max_index_length, "Maximum supported index length is 5!"); - ARM_COMPUTE_RETURN_ERROR_ON(index_len != dst_dims - upt_dims + 1); + ARM_COMPUTE_RETURN_ERROR_ON_MSG( + index_len >= dst_dims && dst_dims != 1, + "Index length should be smaller than number of output dims (or equal to with 1D output)"); return Status{}; } @@ -96,7 +117,7 @@ void ClScatterKernel::configure(const ClCompileContext &compile_context, const TensorShape &dst_shape = dst->tensor_shape(); - const bool is_scalar_block = updates->num_dimensions() == 1; + const bool is_scalar_block = updates->num_dimensions() == 1; // Checks for replacing only a single element. const int n0 = adjust_vec_size(16 / updates->element_size(), is_scalar_block ? 1 : updates->dimension(0)); const int partial_n0 = updates->dimension(0) % n0; @@ -120,9 +141,9 @@ void ClScatterKernel::configure(const ClCompileContext &compile_context, build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(dst->data_type())); build_opts.add_option_if(is_data_type_float(dst->data_type()), "-DIS_FLOAT"); - const int num_dims = dst->num_dimensions(); - - build_opts.add_option("-DNUM_INDICES=" + support::cpp11::to_string(indices->dimension(1))); + const int num_dims = dst->num_dimensions(); + TensorShape ind_collapsed = indices->tensor_shape().collapsed_from(1); + build_opts.add_option("-DNUM_INDICES=" + support::cpp11::to_string(ind_collapsed[1])); build_opts.add_option("-DINDEX_LENGTH=" + support::cpp11::to_string(index_len)); // We provide 5 variables to use in a constant array @@ -187,11 +208,14 @@ void ClScatterKernel::run_op(ITensorPack &tensors, const Window &window, cl::Com const ITensorInfo *dst_info = dst->info(); const int num_dims = dst_info->num_dimensions(); + const int ind_dims = indices->info()->num_dimensions(); const int index_len = indices->info()->dimension(0); // calculate m-dimensional data block strides in updates and destination tensors - const int upt_block_stride = updates->info()->strides_in_bytes()[updates->info()->num_dimensions() - 1]; + const int upt_block_stride = + updates->info()->strides_in_bytes()[updates->info()->num_dimensions() - (ind_dims - 1)]; + const int out_block_stride = dst_info->strides_in_bytes()[num_dims - index_len]; unsigned int idx = 0; |