Remove fixed format strides hack

- Remove hack in CpuGemmAssemblyDispatch.cpp which tried to guess
  strides for fixed format kernels. Instead, expect that strides will
  have been correctly set on weights externally
- Update fixed format test fixtures to set the strides
- If the fixed format uses fast math mode, then weights should be of
  type BFLOAT16. Change the validation logic to accept this.

Resolves: [ONCPUML-1131]

Co-authored-by: Milos Puzovic <Milos.Puzovic@arm.com>
Change-Id: I0f18d8b86b0f639be25fd122fa06a591e90645f2
Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8985
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 15 insertions, 2 deletions

diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
index 63e6dc9377..5b8963ebfe 100644
--- a/tests/validation/fixtures/ConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2022 Arm Limited.
+ * Copyright (c) 2017-2023 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -416,8 +416,21 @@ inline TensorInfo prepare_weights(const TensorInfo tensor_info, const arm_comput
     const int Ip            = arm_gemm::roundup<unsigned int>(C, block_by);      // C'=I'
     const int Op            = arm_gemm::roundup<unsigned int>(N, interleave_by); // O'=N'
 
+    arm_compute::Strides strides_in_bytes = tensor_info.strides_in_bytes();
+    strides_in_bytes.set(1, Ip * interleave_by * H * W * tensor_info.element_size());
+    strides_in_bytes.set(2, Ip * Op * tensor_info.element_size());
+
+    const size_t offset_first_element_in_bytes = tensor_info.offset_first_element_in_bytes();
+
+    // Total size needs to include padded dimensions
+    const size_t total_size_in_bytes = Op * H * W * Ip * tensor_info.element_size();
+
     const TensorShape TS(Ip, W, H, Op);
-    return TensorInfo(TS, 1 /*num_channels*/, data_type, data_layout);
+
+    TensorInfo new_tensor_info = tensor_info;
+    new_tensor_info.init(TS, 1 /*num_channels, deprecated*/, data_type, strides_in_bytes,
+        offset_first_element_in_bytes, total_size_in_bytes);
+    return new_tensor_info;
 }
 
 template <typename ScalarType, typename AccessorType>