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Adding sub, sigmoid, permute, view_copy ops (#6)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,144 @@ | ||
| /* | ||
| * Copyright (c) Meta Platforms, Inc. and affiliates. | ||
| * All rights reserved. | ||
| * | ||
| * This source code is licensed under the BSD-style license found in the | ||
| * LICENSE file in the root directory of this source tree. | ||
| */ | ||
|
|
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| #include <executorch/kernels/portable/cpu/util/copy_ops_util.h> | ||
| #include <executorch/runtime/kernel/kernel_includes.h> | ||
| #include "kernels.h" | ||
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| namespace torch { | ||
| namespace executor { | ||
| namespace native { | ||
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| using SizesType = exec_aten::SizesType; | ||
| using Tensor = exec_aten::Tensor; | ||
| using IntArrayRef = exec_aten::ArrayRef<int64_t>; | ||
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| namespace { | ||
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| void increment_coordinate_permuted( | ||
| const Tensor& tensor, | ||
| size_t* const coordinate, | ||
| IntArrayRef dims) { | ||
| for (int i = dims.size() - 1; i >= 0; i--) { | ||
| size_t d = dims[i] >= 0 ? dims[i] : dims[i] + tensor.dim(); | ||
| coordinate[d]++; | ||
| if (coordinate[d] == tensor.size(d)) { | ||
| coordinate[d] = 0; | ||
| } else { | ||
| return; | ||
| } | ||
| } | ||
| } | ||
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| } // namespace | ||
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| Tensor& permute_copy_out( | ||
| RuntimeContext& ctx, | ||
| const Tensor& in, | ||
| IntArrayRef dims, | ||
| Tensor& out) { | ||
| (void)ctx; | ||
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| ET_KERNEL_CHECK( | ||
| ctx, check_permute_copy_args(in, dims, out), InvalidArgument, out); | ||
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| Tensor::SizesType expected_out_size[kTensorDimensionLimit]; | ||
| size_t expected_out_dim = 0; | ||
| get_permute_copy_out_target_size( | ||
| in, dims, expected_out_size, &expected_out_dim); | ||
| ET_KERNEL_CHECK( | ||
| ctx, | ||
| resize_tensor(out, {expected_out_size, expected_out_dim}) == Error::Ok, | ||
| InvalidArgument, | ||
| out); | ||
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| const auto in_type = out.scalar_type(); | ||
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| if(in_type == ScalarType::Float) | ||
| { | ||
| WORD32 * p_inp = (WORD32 *)in.const_data_ptr<float>(); | ||
| WORD32 * p_out = (WORD32 *)out.mutable_data_ptr<float>(); | ||
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| WORD32 num_inp_dims = in.dim(); | ||
| WORD32 num_out_dims = num_inp_dims; | ||
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| WORD32 p_inp_shape[5]; | ||
| WORD32 p_out_shape[5]; | ||
| WORD32 p_permute_vec[5]; | ||
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| for(int i = 0; i < num_inp_dims; i++) | ||
| { | ||
| p_inp_shape[i] = in.size(i); | ||
| p_out_shape[i] = in.size(dims[i]); | ||
| p_permute_vec[i] = dims[i]; | ||
| } | ||
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| WORD32 val = xa_nn_transpose_32_32(p_out | ||
| ,p_out_shape | ||
| ,p_inp | ||
| ,p_inp_shape | ||
| ,p_permute_vec | ||
| ,num_out_dims | ||
| ,num_inp_dims); | ||
|
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| } | ||
| else if(in_type == ScalarType::Char) | ||
| { | ||
| WORD8 * p_inp = (WORD8 *)in.const_data_ptr<char>(); | ||
| WORD8 * p_out = (WORD8 *)out.mutable_data_ptr<char>(); | ||
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| WORD32 num_inp_dims = in.dim(); | ||
| WORD32 num_out_dims = num_inp_dims; | ||
|
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| WORD32 p_inp_shape[5]; | ||
| WORD32 p_out_shape[5]; | ||
| WORD32 p_permute_vec[5]; | ||
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| for(int i = 0; i < num_inp_dims; i++) | ||
| { | ||
| p_inp_shape[i] = in.size(i); | ||
| p_out_shape[i] = in.size(dims[i]); | ||
| p_permute_vec[i] = dims[i]; | ||
| } | ||
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| p_inp_shape[num_inp_dims] = 4; | ||
| p_out_shape[num_inp_dims] = 4; | ||
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| WORD32 val = xa_nn_transpose_8_8(p_out | ||
| ,p_out_shape | ||
| ,p_inp | ||
| ,p_inp_shape | ||
| ,p_permute_vec | ||
| ,num_out_dims | ||
| ,num_inp_dims); | ||
|
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| } | ||
| else | ||
| { | ||
| // in and out must be the same dtype | ||
| ET_SWITCH_ALL_TYPES(in_type, ctx, "permute_copy.out", CTYPE, [&] { | ||
| const CTYPE* const in_data = in.const_data_ptr<CTYPE>(); | ||
| CTYPE* const out_data = out.mutable_data_ptr<CTYPE>(); | ||
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| size_t in_coord[kTensorDimensionLimit] = {0}; | ||
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| for (size_t i = 0; i < out.numel(); ++i) { | ||
| out_data[i] = in_data[coordinateToIndex(in, in_coord)]; | ||
| increment_coordinate_permuted(in, in_coord, dims); | ||
| } | ||
| }); | ||
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| } | ||
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| return out; | ||
| } | ||
|
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| } // namespace native | ||
| } // namespace executor | ||
| } // namespace torch |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,68 @@ | ||
| /* | ||
| * Copyright (c) Meta Platforms, Inc. and affiliates. | ||
| * All rights reserved. | ||
| * | ||
| * This source code is licensed under the BSD-style license found in the | ||
| * LICENSE file in the root directory of this source tree. | ||
| */ | ||
|
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| #include <cmath> | ||
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| #include <executorch/kernels/portable/cpu/util/functional_util.h> | ||
| #include <executorch/runtime/kernel/kernel_includes.h> | ||
| #include "kernels.h" | ||
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| namespace torch { | ||
| namespace executor { | ||
| namespace native { | ||
|
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| using Tensor = exec_aten::Tensor; | ||
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| Tensor& sigmoid_out(RuntimeContext& ctx, const Tensor& in, Tensor& out) { | ||
| (void)ctx; | ||
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| ET_KERNEL_CHECK( | ||
| ctx, in.scalar_type() != ScalarType::Bool, InvalidArgument, out); | ||
| ET_KERNEL_CHECK(ctx, tensor_is_floating_type(out), InvalidArgument, out); | ||
|
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| // Resize for dynamic shape | ||
| ET_KERNEL_CHECK_MSG( | ||
| ctx, | ||
| resize_tensor(out, in.sizes()) == Error::Ok, | ||
| InvalidArgument, | ||
| out, | ||
| "Failed to resize output tensor."); | ||
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| ScalarType in_type = in.scalar_type(); | ||
| ScalarType out_type = out.scalar_type(); | ||
|
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| if(in_type == ScalarType::Float) | ||
| { | ||
| float* data_in = in.mutable_data_ptr<float>(); | ||
| float* data_out = out.mutable_data_ptr<float>(); | ||
| xa_nn_vec_sigmoid_f32_f32(data_out, data_in, in.numel()); | ||
| } | ||
| else | ||
| { | ||
| ET_SWITCH_REALHB_TYPES(in_type, ctx, "sigmoid.out", CTYPE_IN, [&]() { | ||
| ET_SWITCH_FLOATH_TYPES(out_type, ctx, "sigmoid.out", CTYPE_OUT, [&]() { | ||
| apply_unary_map_fn( | ||
| [](const CTYPE_IN val_in) { | ||
| // perform math in double to preserve precision | ||
| double in_casted = static_cast<double>(val_in); | ||
| double out_val = 1.0 / (1.0 + exp(-in_casted)); | ||
| return static_cast<CTYPE_OUT>(out_val); | ||
| }, | ||
| in.const_data_ptr<CTYPE_IN>(), | ||
| out.mutable_data_ptr<CTYPE_OUT>(), | ||
| in.numel()); | ||
| }); | ||
| }); | ||
| } | ||
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| return out; | ||
| } | ||
|
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| } // namespace native | ||
| } // namespace executor | ||
| } // namespace torch |
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