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| author | Renato Arantes <renato.arantes@arm.com> | 2023-04-24 07:19:59 +0000 |
|---|---|---|
| committer | Renato Barros Arantes <renato.arantes@arm.com> | 2023-05-03 16:12:48 +0000 |
| commit | 57132943e0df00aa008b90614ea5a9fa8b2dc18a (patch) | |
| tree | a6db3f93c399a6832ca7d487c38572bba0aea22a /src/cpu/operators/CpuGemm.cpp | |
| parent | cdd1e039ad598aec10d8c1b81e08de9412324bf2 (diff) | |
| download | ComputeLibrary-57132943e0df00aa008b90614ea5a9fa8b2dc18a.tar.gz | |
Fix im2col for fast-maths mode with padding.
Following the investigation proposed by ONCPUML-1193, padding
is implemented in im2col when the input channel is not a multiple of
blocks requested by the weight format.
Partially resolves: ONCPUML-1193
Signed-off-by: Renato Arantes <renato.arantes@arm.com>
Change-Id: I350c7a1b2dcae63f8d94f5b6f1f86e948eab1f09
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9508
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/cpu/operators/CpuGemm.cpp')
| -rw-r--r-- | src/cpu/operators/CpuGemm.cpp | 23 |
1 files changed, 20 insertions, 3 deletions
diff --git a/src/cpu/operators/CpuGemm.cpp b/src/cpu/operators/CpuGemm.cpp index b9d18c4cb6..7411d763b4 100644 --- a/src/cpu/operators/CpuGemm.cpp +++ b/src/cpu/operators/CpuGemm.cpp @@ -155,14 +155,14 @@ void CpuGemm::configure(const ITensorInfo *a, const ITensorInfo *b, const ITenso Status CpuGemm::validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *d, float alpha, float beta, const GEMMInfo &gemm_info) { ARM_COMPUTE_UNUSED(alpha); - const bool is_c_bias = beta == 1 && c != nullptr; + const bool is_c_bias = beta == 1 && c != nullptr; const bool run_addition = c != nullptr && beta != 0 && beta != 1; ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(a); ARM_COMPUTE_RETURN_ERROR_ON_CPU_BF16_UNSUPPORTED(a); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(a, 1, DataType::BFLOAT16, DataType::F16, DataType::F32); - if (is_fixed_format_fast_math(gemm_info.weight_format())) + if(is_fixed_format_fast_math(gemm_info.weight_format())) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(a, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(b, DataType::BFLOAT16); @@ -172,7 +172,24 @@ Status CpuGemm::validate(const ITensorInfo *a, const ITensorInfo *b, const ITens ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(a, b); } - ARM_COMPUTE_RETURN_ERROR_ON_MSG(a->dimension(0) != b->dimension(1), "The product AB is defined only if the number of columns in A is equal to the number of rows in B"); + const int block_by = arm_compute::block_by(gemm_info.weight_format()); + if(block_by > 1) + { + // have to verify bias + const size_t dim0_sz = a->dimension(0); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((dim0_sz % block_by) != 0, ("The matrix A number of columns must be a multiple of block_by=" + std::to_string(block_by)).c_str()); + // a->dimension(0) = kernel_area * input_channel + kernel_area * input_pad_right + // b->dimension(1) = kernel_area * input_channel + // a->dimension(0) = b->dimension(1) + kernel_area * input_pad_right + const size_t input_pad_right = (dim0_sz - b->dimension(1)) % block_by; + const size_t kernel_area = (dim0_sz - b->dimension(1)) / input_pad_right; + ARM_COMPUTE_RETURN_ERROR_ON_MSG((dim0_sz - kernel_area * input_pad_right) != b->dimension(1), "The product AB is defined only if A number of columns and B number of rows are related"); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(a->dimension(0) != b->dimension(1), "The product AB is defined only if the number of columns in A is equal to the number of rows in B"); + } + ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.is_a_reshaped(), "Matrix A already reshaped is not supported"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.is_b_reshaped(), "Matrix B already reshaped is not supported"); if(a->data_type() != DataType::BFLOAT16) |