diff options
Diffstat (limited to 'src')
5 files changed, 381 insertions, 151 deletions
diff --git a/src/core/CL/cl_kernels/batchnormalization_layer.cl b/src/core/CL/cl_kernels/batchnormalization_layer.cl index 0b61b5638c..29b62d3d92 100644 --- a/src/core/CL/cl_kernels/batchnormalization_layer.cl +++ b/src/core/CL/cl_kernels/batchnormalization_layer.cl @@ -93,8 +93,12 @@ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), #endif /* not IN_PLACE */ VECTOR_DECLARATION(mean), VECTOR_DECLARATION(var), +#ifndef USE_DEFAULT_BETA VECTOR_DECLARATION(beta), +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA VECTOR_DECLARATION(gamma), +#endif /* USE_DEFAULT_GAMMA */ float epsilon) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); @@ -103,10 +107,14 @@ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), #else /* IN_PLACE */ Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); #endif /* IN_PLACE */ - Vector mean = CONVERT_TO_VECTOR_STRUCT(mean); - Vector var = CONVERT_TO_VECTOR_STRUCT(var); - Vector beta = CONVERT_TO_VECTOR_STRUCT(beta); + Vector mean = CONVERT_TO_VECTOR_STRUCT(mean); + Vector var = CONVERT_TO_VECTOR_STRUCT(var); +#ifndef USE_DEFAULT_BETA + Vector beta = CONVERT_TO_VECTOR_STRUCT(beta); +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA Vector gamma = CONVERT_TO_VECTOR_STRUCT(gamma); +#endif /* USE_DEFAULT_GAMMA */ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) data = 0; @@ -117,9 +125,7 @@ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) x_bar = 0; VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - gamma_vec = 0; - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - beta_vec = 0; + res = 0; const int current_slice = get_global_id(2); @@ -132,11 +138,22 @@ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), numerator = SUB_OP(data, numerator); x_bar = MUL_OP(numerator, denominator); +#ifndef USE_DEFAULT_GAMMA + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) gamma_vec = *((__global DATA_TYPE *)(gamma.ptr + current_slice * gamma.stride_x)); - beta_vec = *((__global DATA_TYPE *)(beta.ptr + current_slice * beta.stride_x)); + res = MUL_OP(gamma_vec, x_bar); +#else /* USE_DEFAULT_GAMMA */ + // gamma is equal to 1, no need to perform multiplications + res = x_bar; +#endif /* USE_DEFAULT_GAMMA */ + +#ifndef USE_DEFAULT_BETA VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - res = ADD_OP(MUL_OP(gamma_vec, x_bar), beta_vec); + beta_vec = *((__global DATA_TYPE *)(beta.ptr + current_slice * beta.stride_x)); + // beta is not zero, hence we need to perform the addition + res = ADD_OP(res, beta_vec); +#endif /* USE_DEFAULT_BETA */ res = ACTIVATION_FUNC(res); @@ -144,4 +161,4 @@ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), (res, 0, (__global DATA_TYPE *)out.ptr); } -#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) */
\ No newline at end of file +#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) */ diff --git a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp index 95c8250ee7..62f21eed96 100644 --- a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp +++ b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp @@ -46,9 +46,22 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, { ARM_COMPUTE_UNUSED(epsilon); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, var, beta, gamma); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var, beta, gamma); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var, beta, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, var); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var); + if(beta != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, beta); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, beta); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, beta); + } + if(gamma != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, gamma); + } + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != mean->dimension(0)); if(act_info.enabled()) { @@ -108,7 +121,7 @@ CLBatchNormalizationLayerKernel::CLBatchNormalizationLayerKernel() void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon, ActivationLayerInfo act_info) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, var, beta, gamma); + ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, var); _input = input; _output = output; @@ -120,15 +133,9 @@ void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *out _run_in_place = (output == nullptr) || (output == input); - if(output != nullptr) - { - ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), output->info()); - // Output tensor auto initialization if not yet initialized - auto_init_if_empty(*output->info(), *input->info()->clone()); - } - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (output != nullptr) ? output->info() : nullptr, - mean->info(), var->info(), beta->info(), gamma->info(), epsilon, act_info)); + mean->info(), var->info(), (beta != nullptr) ? beta->info() : nullptr, + (gamma != nullptr) ? gamma->info() : nullptr, epsilon, act_info)); const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); @@ -141,13 +148,23 @@ void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *out build_opts.add_option_if(act_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); build_opts.add_option_if(_run_in_place, "-DIN_PLACE"); build_opts.add_option_if(is_data_type_fixed_point(input->info()->data_type()), "-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position())); + build_opts.add_option_if(beta == nullptr, "-DUSE_DEFAULT_BETA"); + build_opts.add_option_if(gamma == nullptr, "-DUSE_DEFAULT_GAMMA"); // Create kernel _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("batchnormalization_layer", build_opts.options())); // Set kernel static arguments unsigned int include_output = (!_run_in_place) ? 1 : 0; - unsigned int idx = (1 + include_output) * num_arguments_per_3D_tensor() + 4 * num_arguments_per_1D_tensor(); // Skip the input and output parameters + unsigned int idx = (1 + include_output) * num_arguments_per_3D_tensor() + 2 * num_arguments_per_1D_tensor(); // Skip the input and output parameters + if(_beta != nullptr) + { + idx += num_arguments_per_1D_tensor(); // Skip beta parameter + } + if(_gamma != nullptr) + { + idx += num_arguments_per_1D_tensor(); // Skip gamma parameter + } _kernel.setArg<cl_float>(idx++, _epsilon); // Configure kernel window @@ -191,8 +208,14 @@ void CLBatchNormalizationLayerKernel::run(const Window &window, cl::CommandQueue unsigned int idx = (1 + include_output) * num_arguments_per_3D_tensor(); add_1D_tensor_argument(idx, _mean, vector_slice); add_1D_tensor_argument(idx, _var, vector_slice); - add_1D_tensor_argument(idx, _beta, vector_slice); - add_1D_tensor_argument(idx, _gamma, vector_slice); + if(_beta != nullptr) + { + add_1D_tensor_argument(idx, _beta, vector_slice); + } + if(_gamma != nullptr) + { + add_1D_tensor_argument(idx, _gamma, vector_slice); + } do { diff --git a/src/core/GLES_COMPUTE/cs_shaders/batchnormalization_layer.cs b/src/core/GLES_COMPUTE/cs_shaders/batchnormalization_layer.cs index 7629b255b7..81be9679b2 100644 --- a/src/core/GLES_COMPUTE/cs_shaders/batchnormalization_layer.cs +++ b/src/core/GLES_COMPUTE/cs_shaders/batchnormalization_layer.cs @@ -50,6 +50,8 @@ precision mediump float; * * @note The data type must be passed at compile time using "#define DATA_TYPE_NAME". e.g. "#define DATA_TYPE_FP32" * @note Epsilon parameter in the batch normalization equation should be given as a preprocessor argument using "#define EPSILON". e.g. "#define EPSILON 0.1" + * @note Beta is optional with default value of 0. If not provided, the preprocessor argument "USE_DEFAULT_BETA" should be given + * @note Gamma is optional with default value of 1. If not provided, the preprocessor argument "USE_DEFAULT_GAMMA" should be given * * @param[in] src_ptr Pointer to the first source tensor. Supported data types: F16/F32 * @param[in] src_attrs The attributes of the source tensor @@ -59,10 +61,10 @@ precision mediump float; * @param[in] mean_attrs The attributes of the mean tensor * @param[in] var_ptr Pointer to the var tensor. Supported data types: same as @p src_ptr * @param[in] var_attrs The attributes of the var tensor - * @param[in] beta_ptr Pointer to the beta source tensor. Supported data types: same as @p src_ptr - * @param[in] beta_attrs The attributes of the beta tensor - * @param[in] gamma_ptr Pointer to the gamma source tensor. Supported data types: same as @p src_ptr - * @param[in] gamma_attrs The attributes of the gamma tensor + * @param[in] beta_ptr (Optional) Pointer to the beta source tensor. If not provided, default value of beta is 0. Supported data types: same as @p src_ptr + * @param[in] beta_attrs (Optional) The attributes of the beta tensor + * @param[in] gamma_ptr (Optional) Pointer to the gamma source tensor. If not provided, default value of gamma is 1. Supported data types: same as @p src_ptr + * @param[in] gamma_attrs (Optional) The attributes of the gamma tensor */ SHADER_PARAMS_DECLARATION { @@ -70,8 +72,12 @@ SHADER_PARAMS_DECLARATION Tensor3DAttributes dst_attrs; VectorAttributes mean_attrs; VectorAttributes var_attrs; - VectorAttributes beta_attrs; - VectorAttributes gamma_attrs; +#ifndef USE_DEFAULT_BETA + VectorAttributes beta_attrs; +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA + VectorAttributes gamma_attrs; +#endif /* USE_DEFAULT_GAMMA */ }; #ifdef DATA_TYPE_FP32 @@ -79,24 +85,34 @@ TENSOR_DECLARATION(1, srcBuffer, float, src_ptr, src_shift, 2, readonly); TENSOR_DECLARATION(2, dstBuffer, float, dst_ptr, dst_shift, 2, writeonly); TENSOR_DECLARATION(3, meanBuffer, float, mean_ptr, mean_shift, 2, readonly); TENSOR_DECLARATION(4, varBuffer, float, var_ptr, var_shift, 2, readonly); +#ifndef USE_DEFAULT_BETA TENSOR_DECLARATION(5, betaBuffer, float, beta_ptr, beta_shift, 2, readonly); +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA +#ifdef USE_DEFAULT_BETA +TENSOR_DECLARATION(5, gammaBuffer, float, gamma_ptr, gamma_shift, 2, readonly); +#else /* USE_DEFAULT_BETA */ TENSOR_DECLARATION(6, gammaBuffer, float, gamma_ptr, gamma_shift, 2, readonly); +#endif /* USE_DEFAULT_BETA */ +#endif /* USE_DEFAULT_GAMMA */ void main(void) { - Tensor3DIterator src_iter = CONVERT_TO_TENSOR3D_ITERATOR(src_attrs, src_shift); - Tensor3DIterator dst_iter = CONVERT_TO_TENSOR3D_ITERATOR(dst_attrs, dst_shift); - VectorIterator mean_iter = CONVERT_TO_VECTOR_ITERATOR(mean_attrs, mean_shift); - VectorIterator var_iter = CONVERT_TO_VECTOR_ITERATOR(var_attrs, var_shift); - VectorIterator beta_iter = CONVERT_TO_VECTOR_ITERATOR(beta_attrs, beta_shift); - VectorIterator gamma_iter = CONVERT_TO_VECTOR_ITERATOR(gamma_attrs, gamma_shift); + Tensor3DIterator src_iter = CONVERT_TO_TENSOR3D_ITERATOR(src_attrs, src_shift); + Tensor3DIterator dst_iter = CONVERT_TO_TENSOR3D_ITERATOR(dst_attrs, dst_shift); + VectorIterator mean_iter = CONVERT_TO_VECTOR_ITERATOR(mean_attrs, mean_shift); + VectorIterator var_iter = CONVERT_TO_VECTOR_ITERATOR(var_attrs, var_shift); +#ifndef USE_DEFAULT_BETA + VectorIterator beta_iter = CONVERT_TO_VECTOR_ITERATOR(beta_attrs, beta_shift); +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA + VectorIterator gamma_iter = CONVERT_TO_VECTOR_ITERATOR(gamma_attrs, gamma_shift); +#endif /* USE_DEFAULT_GAMMA */ float input_value = 0.f; float denominator = 0.f; float numerator = 0.f; float x_bar = 0.f; - float gamma_param = 0.f; - float beta_param = 0.f; uint current_slice = gl_GlobalInvocationID.z; @@ -109,10 +125,18 @@ void main(void) numerator = SUB_OP(input_value, numerator); x_bar = MUL_OP(numerator, denominator); - gamma_param = LOAD(gamma_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(gamma_iter, current_slice * beta_attrs.stride_x)); - beta_param = LOAD(beta_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(beta_iter, current_slice * beta_attrs.stride_x)); +#ifndef USE_DEFAULT_GAMMA + float gamma_param = LOAD(gamma_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(gamma_iter, current_slice * gamma_attrs.stride_x)); + + x_bar = MUL_OP(gamma_param, x_bar); +#endif /* USE_DEFAULT_GAMMA */ +#ifndef USE_DEFAULT_BETA + float beta_param = LOAD(beta_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(beta_iter, current_slice * beta_attrs.stride_x)); + + x_bar = ADD_OP(x_bar, beta_param); +#endif /* USE_DEFAULT_BETA */ - STORE_CURRENT_ITEM(dst_ptr, dst_iter, ACTIVATION_FUNC(ADD_OP(MUL_OP(gamma_param, x_bar), beta_param))); + STORE_CURRENT_ITEM(dst_ptr, dst_iter, ACTIVATION_FUNC(x_bar)); } #elif defined(DATA_TYPE_FP16) @@ -120,8 +144,16 @@ TENSOR_DECLARATION(1, srcBuffer, uvec2, src_ptr, src_shift, 3, readonly); TENSOR_DECLARATION(2, dstBuffer, uvec2, dst_ptr, dst_shift, 3, writeonly); TENSOR_DECLARATION(3, meanBuffer, uvec2, mean_ptr, mean_shift, 3, readonly); TENSOR_DECLARATION(4, varBuffer, uvec2, var_ptr, var_shift, 3, readonly); +#ifndef USE_DEFAULT_BETA TENSOR_DECLARATION(5, betaBuffer, uvec2, beta_ptr, beta_shift, 3, readonly); +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA +#ifdef USE_DEFAULT_BETA +TENSOR_DECLARATION(5, gammaBuffer, uvec2, gamma_ptr, gamma_shift, 3, readonly); +#else /* USE_DEFAULT_BETA */ TENSOR_DECLARATION(6, gammaBuffer, uvec2, gamma_ptr, gamma_shift, 3, readonly); +#endif /* USE_DEFAULT_BETA */ +#endif /* USE_DEFAULT_GAMMA */ void main(void) { @@ -129,14 +161,18 @@ void main(void) Tensor3DIterator dst_iter = CONVERT_TO_TENSOR3D_ITERATOR(dst_attrs, dst_shift); VectorIterator mean_iter = CONVERT_TO_VECTOR_ITERATOR(mean_attrs, mean_shift); VectorIterator var_iter = CONVERT_TO_VECTOR_ITERATOR(var_attrs, var_shift); +#ifndef USE_DEFAULT_BETA VectorIterator beta_iter = CONVERT_TO_VECTOR_ITERATOR(beta_attrs, beta_shift); +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_GAMMA VectorIterator gamma_iter = CONVERT_TO_VECTOR_ITERATOR(gamma_attrs, gamma_shift); +#endif /* USE_DEFAULT_GAMMA */ vec4 unpacked_s[5]; float denominator; float numerator; - float gamma_param; - float beta_param; + float gamma_param = 1.f; + float beta_param = 0.f; vec4 x_bar; vec4 result; @@ -144,68 +180,87 @@ void main(void) unpacked_s[0] = LOAD_UNPACK4_CURRENT_ITEM_HALF(src_ptr, src_iter); unpacked_s[1] = LOAD_UNPACK4_HALF(var_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(var_iter, current_slice * var_attrs.stride_x)); unpacked_s[2] = LOAD_UNPACK4_HALF(mean_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(mean_iter, current_slice * mean_attrs.stride_x)); - unpacked_s[3] = LOAD_UNPACK4_HALF(gamma_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(gamma_iter, current_slice * beta_attrs.stride_x)); +#ifndef USE_DEFAULT_GAMMA + unpacked_s[3] = LOAD_UNPACK4_HALF(gamma_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(gamma_iter, current_slice * gamma_attrs.stride_x)); +#endif /* USE_DEFAULT_BETA */ +#ifndef USE_DEFAULT_BETA unpacked_s[4] = LOAD_UNPACK4_HALF(beta_ptr, TENSOR_OFFSET_ADVANCE_IN_BYTES(beta_iter, current_slice * beta_attrs.stride_x)); +#endif /* USE_DEFAULT_GAMMA */ if((current_slice % uint(4)) == uint(0)) { denominator = unpacked_s[1].x; denominator = INVSQRT_OP(ADD_OP(denominator, SQCVT_SAT(float(ESPILON)))); - //Calculate x bar and store results - numerator = unpacked_s[2].x; - x_bar = MUL_OP(SUB_OP(unpacked_s[0], numerator), denominator); + // Calculate x bar + numerator = unpacked_s[2].x; + x_bar = MUL_OP(SUB_OP(unpacked_s[0], numerator), denominator); +#ifndef USE_DEFAULT_GAMMA gamma_param = unpacked_s[3].x; +#endif /* USE_DEFAULT_GAMMA */ +#ifndef USE_DEFAULT_BETA beta_param = unpacked_s[4].x; - result = ACTIVATION_FUNC(ADD_OP(MUL_OP(gamma_param, x_bar), beta_param)); - - STORE_PACK4_CURRENT_ITEM_HALF(dst_ptr, dst_iter, result); +#endif /* USE_DEFAULT_BETA */ } else if((current_slice % uint(4)) == uint(1)) { denominator = unpacked_s[1].y; denominator = INVSQRT_OP(ADD_OP(denominator, SQCVT_SAT(float(ESPILON)))); - //Calculate x bar and store results - numerator = unpacked_s[2].y; - x_bar = MUL_OP(SUB_OP(unpacked_s[0], numerator), denominator); + // Calculate x bar + numerator = unpacked_s[2].y; + x_bar = MUL_OP(SUB_OP(unpacked_s[0], numerator), denominator); +#ifndef USE_DEFAULT_GAMMA gamma_param = unpacked_s[3].y; +#endif /* USE_DEFAULT_GAMMA */ +#ifndef USE_DEFAULT_BETA beta_param = unpacked_s[4].y; - result = ACTIVATION_FUNC(ADD_OP(MUL_OP(gamma_param, x_bar), beta_param)); - - STORE_PACK4_CURRENT_ITEM_HALF(dst_ptr, dst_iter, result); +#endif /* USE_DEFAULT_BETA */ } else if((current_slice % uint(4)) == uint(2)) { denominator = unpacked_s[1].z; denominator = INVSQRT_OP(ADD_OP(denominator, SQCVT_SAT(float(ESPILON)))); - //Calculate x bar and store results - numerator = unpacked_s[2].z; - x_bar = MUL_OP(SUB_OP(unpacked_s[0], numerator), denominator); + // Calculate x bar + numerator = unpacked_s[2].z; + x_bar = MUL_OP(SUB_OP(unpacked_s[0], numerator), denominator); +#ifndef USE_DEFAULT_GAMMA gamma_param = unpacked_s[3].z; +#endif /* USE_DEFAULT_GAMMA */ +#ifndef USE_DEFAULT_BETA beta_param = unpacked_s[4].z; - result = ACTIVATION_FUNC(ADD_OP(MUL_OP(gamma_param, x_bar), beta_param)); - - STORE_PACK4_CURRENT_ITEM_HALF(dst_ptr, dst_iter, result); +#endif /* USE_DEFAULT_BETA */ } else { denominator = unpacked_s[1].w; denominator = INVSQRT_OP(ADD_OP(denominator, SQCVT_SAT(float(ESPILON)))); - //Calculate x bar and store results - numerator = unpacked_s[2].w; - x_bar = MUL_OP(SUB_OP(unpacked_s[0], numerator), denominator); + // Calculate x bar + numerator = unpacked_s[2].w; + x_bar = MUL_OP(SUB_OP(unpacked_s[0], numerator), denominator); +#ifndef USE_DEFAULT_GAMMA gamma_param = unpacked_s[3].w; +#endif /* USE_DEFAULT_GAMMA */ +#ifndef USE_DEFAULT_BETA beta_param = unpacked_s[4].w; - result = ACTIVATION_FUNC(ADD_OP(MUL_OP(gamma_param, x_bar), beta_param)); - - STORE_PACK4_CURRENT_ITEM_HALF(dst_ptr, dst_iter, result); +#endif /* USE_DEFAULT_BETA */ } + +#ifndef USE_DEFAULT_GAMMA + x_bar = MUL_OP(gamma_param, x_bar); +#endif /* USE_DEFAULT_GAMMA */ +#ifndef USE_DEFAULT_BETA + x_bar = ADD_OP(x_bar, beta_param); +#endif /* USE_DEFAULT_BETA */ + + result = ACTIVATION_FUNC(x_bar); + + STORE_PACK4_CURRENT_ITEM_HALF(dst_ptr, dst_iter, result); } #endif /*DATA_TYPE_FP16*/ diff --git a/src/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.cpp b/src/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.cpp index cd93f6997e..9a592dfe00 100644 --- a/src/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.cpp +++ b/src/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.cpp @@ -36,32 +36,118 @@ using namespace arm_compute; -GCBatchNormalizationLayerKernel::GCBatchNormalizationLayerKernel() - : _input(nullptr), _output(nullptr), _mean(nullptr), _var(nullptr), _beta(nullptr), _gamma(nullptr), _epsilon(0.0f) +namespace { -} - -void GCBatchNormalizationLayerKernel::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, - float epsilon, ActivationLayerInfo act_info) +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, + const ITensorInfo *mean, const ITensorInfo *var, + const ITensorInfo *beta, const ITensorInfo *gamma, + float epsilon, ActivationLayerInfo act_info) { + ARM_COMPUTE_UNUSED(epsilon); + ARM_COMPUTE_UNUSED(var); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_NULLPTR(output); - // Output tensor auto initialization if not yet initialized - auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var); + ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(mean, var); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, mean, var, beta, gamma); - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output, mean, var, beta, gamma); - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(mean, var, beta, gamma); + if(output->total_size() != 0) + { + ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); + } + + if(beta != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, beta); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, beta); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, beta); + } + if(gamma != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, gamma); + } if(act_info.enabled()) { - ARM_COMPUTE_ERROR_ON(input->info()->data_type() != DataType::F32 && input->info()->data_type() != DataType::F16); + ARM_COMPUTE_ERROR_ON(input->data_type() != DataType::F32 && input->data_type() != DataType::F16); ARM_COMPUTE_ERROR_ON(act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::RELU && act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU && act_info.activation() != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU); ARM_COMPUTE_ERROR_ON(act_info.b() > act_info.a()); } + return Status{}; +} + +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, + ITensorInfo *mean, ITensorInfo *var, + ITensorInfo *beta, ITensorInfo *gamma) +{ + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type(), input->fixed_point_position()); + + unsigned int num_elems_processed_per_iteration = 1; + if(input->data_type() == DataType::F16) + { + num_elems_processed_per_iteration = 4; + } + + // Configure kernel window + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + + AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + AccessWindowStatic mean_access(mean, 0, 0, mean->dimension(0) + 3, mean->dimension(1)); + AccessWindowStatic var_access(var, 0, 0, var->dimension(0) + 3, var->dimension(1)); + + bool window_changed = false; + if(beta != nullptr) + { + AccessWindowStatic beta_access(beta, 0, 0, beta->dimension(0) + 3, beta->dimension(1)); + if(gamma != nullptr) + { + AccessWindowStatic gamma_access(gamma, 0, 0, gamma->dimension(0) + 3, gamma->dimension(1)); + window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, beta_access, gamma_access); + } + else + { + window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, beta_access); + } + } + else + { + if(gamma != nullptr) + { + AccessWindowStatic gamma_access(gamma, 0, 0, gamma->dimension(0) + 3, gamma->dimension(1)); + window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access, gamma_access); + } + else + { + window_changed = update_window_and_padding(win, input_access, output_access, mean_access, var_access); + } + } + output_access.set_valid_region(win, input->valid_region()); + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win); +} +} // namespace + +GCBatchNormalizationLayerKernel::GCBatchNormalizationLayerKernel() + : _input(nullptr), _output(nullptr), _mean(nullptr), _var(nullptr), _beta(nullptr), _gamma(nullptr), _epsilon(0.0f) +{ +} + +void GCBatchNormalizationLayerKernel::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, + float epsilon, ActivationLayerInfo act_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, var); + + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), var->info(), + (beta != nullptr) ? beta->info() : nullptr, (gamma != nullptr) ? gamma->info() : nullptr, + epsilon, act_info)); _input = input; _output = output; @@ -71,12 +157,6 @@ void GCBatchNormalizationLayerKernel::configure(const IGCTensor *input, IGCTenso _gamma = gamma; _epsilon = epsilon; - unsigned int num_elems_processed_per_iteration = 1; - if(input->info()->data_type() == DataType::F16) - { - num_elems_processed_per_iteration = 4; - } - // Set build options std::set<std::string> build_opts; std::string dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16"; @@ -85,6 +165,14 @@ void GCBatchNormalizationLayerKernel::configure(const IGCTensor *input, IGCTenso build_opts.emplace(("#define LOCAL_SIZE_X " + support::cpp11::to_string(1))); build_opts.emplace(("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1))); build_opts.emplace(("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1))); + if(beta == nullptr) + { + build_opts.emplace("#define USE_DEFAULT_BETA"); + } + if(gamma == nullptr) + { + build_opts.emplace("#define USE_DEFAULT_GAMMA"); + } if(act_info.enabled()) { @@ -97,19 +185,25 @@ void GCBatchNormalizationLayerKernel::configure(const IGCTensor *input, IGCTenso _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("batchnormalization_layer", build_opts)); // Configure kernel window - Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); + auto win_config = validate_and_configure_window(input->info(), output->info(), mean->info(), var->info(), + (beta != nullptr) ? beta->info() : nullptr, (gamma != nullptr) ? gamma->info() : nullptr); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); - AccessWindowStatic mean_access(mean->info(), 0, 0, mean->info()->dimension(0) + 3, mean->info()->dimension(1)); - AccessWindowStatic var_access(var->info(), 0, 0, var->info()->dimension(0) + 3, var->info()->dimension(1)); - AccessWindowStatic beta_access(beta->info(), 0, 0, beta->info()->dimension(0) + 3, beta->info()->dimension(1)); - AccessWindowStatic gamma_access(gamma->info(), 0, 0, gamma->info()->dimension(0) + 3, gamma->info()->dimension(1)); + IGCKernel::configure(win_config.second); +} - update_window_and_padding(win, input_access, output_access, mean_access, var_access, beta_access, gamma_access); - output_access.set_valid_region(win, input->info()->valid_region()); +Status GCBatchNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, + const ITensorInfo *mean, const ITensorInfo *var, + const ITensorInfo *beta, const ITensorInfo *gamma, + float epsilon, ActivationLayerInfo act_info) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mean, var, beta, gamma, epsilon, act_info)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), + mean->clone().get(), var->clone().get(), + beta->clone().get(), gamma->clone().get()) + .first); - IGCKernel::configure(win); + return Status{}; } void GCBatchNormalizationLayerKernel::run(const Window &window) @@ -127,11 +221,18 @@ void GCBatchNormalizationLayerKernel::run(const Window &window) Window vector_slice = window.first_slice_window_1D(); vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); - unsigned int idx = 2 * num_arguments_per_3D_tensor(); - add_1D_tensor_argument(idx, _mean, 3, vector_slice); - add_1D_tensor_argument(idx, _var, 4, vector_slice); - add_1D_tensor_argument(idx, _beta, 5, vector_slice); - add_1D_tensor_argument(idx, _gamma, 6, vector_slice); + unsigned int idx = 2 * num_arguments_per_3D_tensor(); + unsigned int binding_point = 3; + add_1D_tensor_argument(idx, _mean, binding_point, vector_slice); + add_1D_tensor_argument(idx, _var, ++binding_point, vector_slice); + if(_beta != nullptr) + { + add_1D_tensor_argument(idx, _beta, ++binding_point, vector_slice); + } + if(_gamma != nullptr) + { + add_1D_tensor_argument(idx, _gamma, ++binding_point, vector_slice); + } slice.shift(Window::DimX, -(_output->info()->padding()).left); diff --git a/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.cpp b/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.cpp index 1f730a2c3c..d1bdfac2da 100644 --- a/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.cpp +++ b/src/core/NEON/kernels/NEBatchNormalizationLayerKernel.cpp @@ -62,9 +62,21 @@ validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const IT ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); } - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var, beta, gamma); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var, beta, gamma); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, var, beta, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, var); + if(beta != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, beta); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, beta); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, beta); + } + if(gamma != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, gamma); + } ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != mean->dimension(0)); return Status{}; @@ -72,6 +84,12 @@ validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const IT std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) { + if(output != nullptr) + { + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output, *input->clone()); + } + unsigned int num_elems_processed_per_iteration = 16 / input->element_size(); Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); @@ -99,13 +117,13 @@ void NEBatchNormalizationLayerKernel::batch_normalization_qs8(const Window &wind const int fixed_point_position = _input->info()->fixed_point_position(); const auto input_mean = reinterpret_cast<const qint8_t *>(_mean->ptr_to_element(Coordinates(0, 0))); const auto input_var = reinterpret_cast<const qint8_t *>(_var->ptr_to_element(Coordinates(0, 0))); - const auto input_gamma = reinterpret_cast<const qint8_t *>(_gamma->ptr_to_element(Coordinates(0, 0))); - const auto input_beta = reinterpret_cast<const qint8_t *>(_beta->ptr_to_element(Coordinates(0, 0))); + const auto input_gamma = (_gamma != nullptr) ? reinterpret_cast<const qint8_t *>(_gamma->ptr_to_element(Coordinates(0, 0))) : nullptr; + const auto input_beta = (_beta != nullptr) ? reinterpret_cast<const qint8_t *>(_beta->ptr_to_element(Coordinates(0, 0))) : nullptr; qint8x16_t mean_vec = vdupq_n_qs8(0); qint8x16_t var_vec = vdupq_n_qs8(0); - qint8x16_t gamma_vec = vdupq_n_qs8(0); - qint8x16_t beta_vec = vdupq_n_qs8(0); + qint8x16_t gamma_vec = vdupq_n_qs8(sqcvt_qs8_f32(1, fixed_point_position)); + qint8x16_t beta_vec = vdupq_n_qs8(sqcvt_qs8_f32(0, fixed_point_position)); qint8x16_t denominator = vdupq_n_qs8(0); const qint8x16_t epsilon_vec = vdupq_n_qs8(sqcvt_qs8_f32(_epsilon, fixed_point_position)); execute_window_loop(window, [&](const Coordinates & id) @@ -113,10 +131,16 @@ void NEBatchNormalizationLayerKernel::batch_normalization_qs8(const Window &wind if(slice != id.z()) { // Conctruct vectors - mean_vec = vdupq_n_qs8(*(input_mean + id.z())); - var_vec = vdupq_n_qs8(*(input_var + id.z())); - gamma_vec = vdupq_n_qs8(*(input_gamma + id.z())); - beta_vec = vdupq_n_qs8(*(input_beta + id.z())); + mean_vec = vdupq_n_qs8(*(input_mean + id.z())); + var_vec = vdupq_n_qs8(*(input_var + id.z())); + if(input_gamma != nullptr) + { + gamma_vec = vdupq_n_qs8(*(input_gamma + id.z())); + } + if(input_beta != nullptr) + { + beta_vec = vdupq_n_qs8(*(input_beta + id.z())); + } // Calculate denominator denominator = vqinvsqrtq_qs8(vqaddq_qs8(var_vec, epsilon_vec), fixed_point_position); @@ -146,13 +170,13 @@ void NEBatchNormalizationLayerKernel::batch_normalization_qs16(const Window &win const int fixed_point_position = _input->info()->fixed_point_position(); const auto input_mean = reinterpret_cast<const qint16_t *>(_mean->ptr_to_element(Coordinates(0, 0))); const auto input_var = reinterpret_cast<const qint16_t *>(_var->ptr_to_element(Coordinates(0, 0))); - const auto input_gamma = reinterpret_cast<const qint16_t *>(_gamma->ptr_to_element(Coordinates(0, 0))); - const auto input_beta = reinterpret_cast<const qint16_t *>(_beta->ptr_to_element(Coordinates(0, 0))); + const auto input_gamma = (_gamma != nullptr) ? reinterpret_cast<const qint16_t *>(_gamma->ptr_to_element(Coordinates(0, 0))) : nullptr; + const auto input_beta = (_beta != nullptr) ? reinterpret_cast<const qint16_t *>(_beta->ptr_to_element(Coordinates(0, 0))) : nullptr; qint16x8_t mean_vec = vdupq_n_qs16(0); qint16x8_t var_vec = vdupq_n_qs16(0); - qint16x8_t gamma_vec = vdupq_n_qs16(0); - qint16x8_t beta_vec = vdupq_n_qs16(0); + qint16x8_t gamma_vec = vdupq_n_qs16(sqcvt_qs16_f32(1, fixed_point_position)); + qint16x8_t beta_vec = vdupq_n_qs16(sqcvt_qs16_f32(0, fixed_point_position)); qint16x8_t denominator = vdupq_n_qs16(0); const qint16x8_t epsilon_vec = vdupq_n_qs16(sqcvt_qs16_f32(_epsilon, fixed_point_position)); execute_window_loop(window, [&](const Coordinates & id) @@ -160,10 +184,16 @@ void NEBatchNormalizationLayerKernel::batch_normalization_qs16(const Window &win if(slice != id.z()) { // Conctruct vectors - mean_vec = vdupq_n_qs16(*(input_mean + id.z())); - var_vec = vdupq_n_qs16(*(input_var + id.z())); - gamma_vec = vdupq_n_qs16(*(input_gamma + id.z())); - beta_vec = vdupq_n_qs16(*(input_beta + id.z())); + mean_vec = vdupq_n_qs16(*(input_mean + id.z())); + var_vec = vdupq_n_qs16(*(input_var + id.z())); + if(input_gamma != nullptr) + { + gamma_vec = vdupq_n_qs16(*(input_gamma + id.z())); + } + if(input_beta != nullptr) + { + beta_vec = vdupq_n_qs16(*(input_beta + id.z())); + } // Calculate denominator denominator = vqinvsqrtq_qs16(vqaddq_qs16(var_vec, epsilon_vec), fixed_point_position); @@ -194,12 +224,12 @@ void NEBatchNormalizationLayerKernel::batch_normalization_fp16(const Window &win const auto input_mean = reinterpret_cast<const float16_t *>(_mean->ptr_to_element(Coordinates(0, 0))); const auto input_var = reinterpret_cast<const float16_t *>(_var->ptr_to_element(Coordinates(0, 0))); - const auto input_gamma = reinterpret_cast<const float16_t *>(_gamma->ptr_to_element(Coordinates(0, 0))); - const auto input_beta = reinterpret_cast<const float16_t *>(_beta->ptr_to_element(Coordinates(0, 0))); + const auto input_gamma = (_gamma != nullptr) ? reinterpret_cast<const float16_t *>(_gamma->ptr_to_element(Coordinates(0, 0))) : nullptr; + const auto input_beta = (_beta != nullptr) ? reinterpret_cast<const float16_t *>(_beta->ptr_to_element(Coordinates(0, 0))) : nullptr; float16x8_t mean_vec = vdupq_n_f16(0.0); float16x8_t var_vec = vdupq_n_f16(0.0); - float16x8_t gamma_vec = vdupq_n_f16(0.0); + float16x8_t gamma_vec = vdupq_n_f16(1.0); float16x8_t beta_vec = vdupq_n_f16(0.0); float16x8_t denominator = vdupq_n_f16(0.0); const float16x8_t epsilon_vec = vdupq_n_f16(_epsilon); @@ -208,10 +238,16 @@ void NEBatchNormalizationLayerKernel::batch_normalization_fp16(const Window &win if(slice != id.z()) { // Conctruct vectors - mean_vec = vdupq_n_f16(*(input_mean + id.z())); - var_vec = vdupq_n_f16(*(input_var + id.z())); - gamma_vec = vdupq_n_f16(*(input_gamma + id.z())); - beta_vec = vdupq_n_f16(*(input_beta + id.z())); + mean_vec = vdupq_n_f16(*(input_mean + id.z())); + var_vec = vdupq_n_f16(*(input_var + id.z())); + if(input_gamma != nullptr) + { + gamma_vec = vdupq_n_f16(*(input_gamma + id.z())); + } + if(input_beta != nullptr) + { + beta_vec = vdupq_n_f16(*(input_beta + id.z())); + } // Calculate denominator denominator = vinvsqrtq_f16(vaddq_f16(var_vec, epsilon_vec)); @@ -241,12 +277,12 @@ void NEBatchNormalizationLayerKernel::batch_normalization_fp32(const Window &win const auto input_mean = reinterpret_cast<const float *>(_mean->ptr_to_element(Coordinates(0, 0))); const auto input_var = reinterpret_cast<const float *>(_var->ptr_to_element(Coordinates(0, 0))); - const auto input_gamma = reinterpret_cast<const float *>(_gamma->ptr_to_element(Coordinates(0, 0))); - const auto input_beta = reinterpret_cast<const float *>(_beta->ptr_to_element(Coordinates(0, 0))); + const auto input_gamma = (_gamma != nullptr) ? reinterpret_cast<const float *>(_gamma->ptr_to_element(Coordinates(0, 0))) : nullptr; + const auto input_beta = (_beta != nullptr) ? reinterpret_cast<const float *>(_beta->ptr_to_element(Coordinates(0, 0))) : nullptr; float32x4_t mean_vec = vdupq_n_f32(0.0); float32x4_t var_vec = vdupq_n_f32(0.0); - float32x4_t gamma_vec = vdupq_n_f32(0.0); + float32x4_t gamma_vec = vdupq_n_f32(1.0); float32x4_t beta_vec = vdupq_n_f32(0.0); float32x4_t denominator = vdupq_n_f32(0.0); const float32x4_t epsilon_vec = vdupq_n_f32(_epsilon); @@ -255,10 +291,16 @@ void NEBatchNormalizationLayerKernel::batch_normalization_fp32(const Window &win if(slice != id.z()) { // Conctruct vectors - mean_vec = vdupq_n_f32(*(input_mean + id.z())); - var_vec = vdupq_n_f32(*(input_var + id.z())); - gamma_vec = vdupq_n_f32(*(input_gamma + id.z())); - beta_vec = vdupq_n_f32(*(input_beta + id.z())); + mean_vec = vdupq_n_f32(*(input_mean + id.z())); + var_vec = vdupq_n_f32(*(input_var + id.z())); + if(input_gamma != nullptr) + { + gamma_vec = vdupq_n_f32(*(input_gamma + id.z())); + } + if(input_beta != nullptr) + { + beta_vec = vdupq_n_f32(*(input_beta + id.z())); + } // Calculate denominator denominator = vinvsqrtq_f32(vaddq_f32(var_vec, epsilon_vec)); @@ -335,21 +377,12 @@ void NEBatchNormalizationLayerKernel::configure(ITensor *input, ITensor *output, const ITensor *beta, const ITensor *gamma, float epsilon, ActivationLayerInfo act_info) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, var, beta, gamma); + ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, var); - ITensorInfo *output_info = nullptr; - - if(nullptr != output) - { - // Output tensor auto initialization if not yet initialized - auto_init_if_empty(*output->info(), *input->info()); - - output_info = output->info(); - } - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output_info, + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (output != nullptr) ? output->info() : nullptr, mean->info(), var->info(), - beta->info(), gamma->info(), + (beta != nullptr) ? beta->info() : nullptr, + (gamma != nullptr) ? gamma->info() : nullptr, epsilon, act_info)); _input = input; @@ -361,7 +394,8 @@ void NEBatchNormalizationLayerKernel::configure(ITensor *input, ITensor *output, _epsilon = epsilon; _act_info = act_info; - if(output != nullptr) + const bool run_in_place = (output == nullptr) || (output == input); + if(!run_in_place) { _output = output; } @@ -377,7 +411,7 @@ void NEBatchNormalizationLayerKernel::configure(ITensor *input, ITensor *output, } // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), output_info); + auto win_config = validate_and_configure_window(input->info(), (run_in_place) ? nullptr : output->info()); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); INEKernel::configure(win_config.second); } |