COMPMID-2398: Add test for CLFuseBatchNormalizationLayer

Change-Id: I786df628ce15fc33fc42c9437fe82972e02e3b16
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1317
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 24 insertions, 42 deletions

diff --git a/src/core/CL/kernels/CLFuseBatchNormalizationKernel.cpp b/src/core/CL/kernels/CLFuseBatchNormalizationKernel.cpp
index 150d9b6d1a..16ad7d970e 100644
--- a/src/core/CL/kernels/CLFuseBatchNormalizationKernel.cpp
+++ b/src/core/CL/kernels/CLFuseBatchNormalizationKernel.cpp
@@ -48,9 +48,9 @@ Status validate_arguments(const ITensorInfo *conv_weights, const ITensorInfo *bn
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(conv_weights, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(bn_mean, bn_var);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(conv_weights, bn_mean, bn_var);
-
-    unsigned int kernels_idx = get_data_layout_dimension_index(conv_weights->data_layout(), DataLayoutDimension::BATCHES);
-    ARM_COMPUTE_RETURN_ERROR_ON(conv_weights->dimension(kernels_idx) != bn_mean->dimension(0));
+    ARM_COMPUTE_RETURN_ERROR_ON(conv_bias == nullptr && fused_bias == nullptr);
+    ARM_COMPUTE_RETURN_ERROR_ON(conv_weights->dimension(3) != bn_mean->dimension(0));
+    ARM_COMPUTE_RETURN_ERROR_ON(bn_mean->num_dimensions() > 1);
 
     // Validate bias
     if(conv_bias != nullptr)
@@ -70,7 +70,6 @@ Status validate_arguments(const ITensorInfo *conv_weights, const ITensorInfo *bn
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(bn_mean, bn_gamma);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(conv_weights, bn_gamma);
     }
-
     // Validate output weights
     if(fused_weights != nullptr && fused_weights->total_size() != 0)
     {
@@ -113,20 +112,18 @@ void CLFuseBatchNormalizationKernel::configure(const ICLTensor *conv_weights, co
     _epsilon       = epsilon;
 
     _run_in_place_weights = (fused_weights == nullptr) || (fused_weights == conv_weights);
-    _run_in_place_bias    = (fused_bias == nullptr) || (conv_bias != nullptr && fused_bias == conv_bias);
+    _run_in_place_bias    = (conv_bias != nullptr && fused_bias == nullptr) || (conv_bias != nullptr && fused_bias == conv_bias);
 
     // Auto initialize outputs
     if(_fused_weights != nullptr)
     {
         // Output tensor auto initialization if not yet initialized
         auto_init_if_empty(*_fused_weights->info(), *_conv_weights->info()->clone());
-        fused_weights->info()->set_valid_region(conv_weights->info()->valid_region());
     }
     if(_fused_bias != nullptr)
     {
         // Output tensor auto initialization if not yet initialized
         auto_init_if_empty(*_fused_bias->info(), *_bn_mean->info()->clone());
-        _fused_bias->info()->set_valid_region(bn_mean->info()->valid_region());
     }
 
     // Validate arguments
@@ -139,35 +136,22 @@ void CLFuseBatchNormalizationKernel::configure(const ICLTensor *conv_weights, co
                                                   epsilon));
 
     // Configure kernel window
-    const unsigned int num_elems_processed_per_iteration_x = 4;
-    const int          output_width_x                      = conv_weights->info()->tensor_shape().x();
-    const bool         multi_access_x                      = (output_width_x / num_elems_processed_per_iteration_x > 0);
-
     Window win = calculate_max_window(*conv_weights->info());
-    if(multi_access_x)
-    {
-        win.set(Window::DimX, Window::Dimension(win.x().start(),
-                                                ceil_to_multiple(win.x().end(), num_elems_processed_per_iteration_x),
-                                                num_elems_processed_per_iteration_x));
-    }
     ICLKernel::configure_internal(win);
 
     // Set build options
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(conv_weights->info()->data_type()));
-    build_opts.add_option("-DSELECT_DATA_TYPE=" + get_cl_select_type_from_data_type(conv_weights->info()->data_type()));
-    build_opts.add_option("-DNUM_CHANNELS=" + support::cpp11::to_string(conv_weights->info()->dimension(2)));
+    build_opts.add_option("-DDIM2=" + support::cpp11::to_string(conv_weights->info()->dimension(2)));
     build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(epsilon));
-    build_opts.add_option_if(multi_access_x, "-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration_x));
-    build_opts.add_option_if(multi_access_x, "-DLAST_ACCESSED_X=" + support::cpp11::to_string(std::max<int>(output_width_x - num_elems_processed_per_iteration_x, 0)));
     build_opts.add_option_if(_run_in_place_weights, "-DIN_PLACE_W");
     build_opts.add_option_if(_run_in_place_bias, "-DIN_PLACE_B");
-    build_opts.add_option_if(conv_bias != nullptr, "-DHAS_BIAS");
-    build_opts.add_option_if(bn_beta == nullptr, "-DUSE_DEFAULT_BETA");
-    build_opts.add_option_if(bn_gamma == nullptr, "-DUSE_DEFAULT_GAMMA");
+    build_opts.add_option_if(conv_bias != nullptr, "-DBIAS");
+    build_opts.add_option_if(bn_beta != nullptr, "-DBETA");
+    build_opts.add_option_if(bn_gamma != nullptr, "-DGAMMA");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("fuse_batchnormalization_layer", build_opts.options()));
+    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("fuse_batchnormalization_conv_layer", build_opts.options()));
 }
 
 Status CLFuseBatchNormalizationKernel::validate(const ITensorInfo *conv_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var,
@@ -185,37 +169,35 @@ void CLFuseBatchNormalizationKernel::run(const arm_compute::Window &window, cl::
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
 
     // Create window slice
-    Window collapsed_window = window.collapse_if_possible(window, Window::DimZ);
-    Window slice            = collapsed_window.first_slice_window_4D();
-
-    Window vector_slice = window.first_slice_window_1D();
-    vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0));
+    Window collapsed_window = window.collapse(window, Window::DimZ);
+    Window slice_1d         = window.first_slice_window_1D();
+    Window slice_3d         = collapsed_window.first_slice_window_3D();
 
     // Add kernel arguments
     unsigned int idx = 0;
-    add_4D_tensor_argument(idx, _conv_weights, slice);
-    add_1D_tensor_argument(idx, _bn_mean, vector_slice);
-    add_1D_tensor_argument(idx, _bn_var, vector_slice);
-    if(!_run_in_place_weights)
+    add_3D_tensor_argument(idx, _conv_weights, slice_3d);
+    if(_conv_bias != nullptr)
     {
-        add_4D_tensor_argument(idx, _fused_weights, slice);
+        add_1D_tensor_argument(idx, _conv_bias, slice_1d);
     }
-    if(!_run_in_place_bias)
+    add_1D_tensor_argument(idx, _bn_mean, slice_1d);
+    add_1D_tensor_argument(idx, _bn_var, slice_1d);
+    if(!_run_in_place_weights)
     {
-        add_1D_tensor_argument(idx, _fused_bias, vector_slice);
+        add_3D_tensor_argument(idx, _fused_weights, slice_3d);
     }
-    if(_conv_bias != nullptr)
+    if(!_run_in_place_bias)
     {
-        add_1D_tensor_argument(idx, _conv_bias, vector_slice);
+        add_1D_tensor_argument(idx, _fused_bias, slice_1d);
     }
     if(_bn_beta != nullptr)
     {
-        add_1D_tensor_argument(idx, _bn_beta, vector_slice);
+        add_1D_tensor_argument(idx, _bn_beta, slice_1d);
     }
     if(_bn_gamma != nullptr)
     {
-        add_1D_tensor_argument(idx, _bn_gamma, vector_slice);
+        add_1D_tensor_argument(idx, _bn_gamma, slice_1d);
     }
-    enqueue(queue, *this, slice);
+    enqueue(queue, *this, slice_3d);
 }
 } // namespace arm_compute