commit 57132943e0df00aa008b90614ea5a9fa8b2dc18a
author Renato Arantes <renato.arantes@arm.com> Mon Apr 24 07:19:59 2023 +0000
committer Renato Barros Arantes <renato.arantes@arm.com> Wed May 03 16:12:48 2023 +0000
tree a6db3f93c399a6832ca7d487c38572bba0aea22a
parent cdd1e039ad598aec10d8c1b81e08de9412324bf2

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>

src/cpu/operators/CpuGemm.cpp

diff --git a/src/cpu/operators/CpuGemm.cpp b/src/cpu/operators/CpuGemm.cpp
index b9d18c4..7411d76 100644
--- a/src/cpu/operators/CpuGemm.cpp
+++ b/src/cpu/operators/CpuGemm.cpp
@@ -155,14 +155,14 @@
 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 @@
         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)