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remove unnecessary parenthesis around lambda functions (pytorch#972)
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Summary:
Pull Request resolved: pytorch#972

Mechanical codemod

Reviewed By: jasonjk-park

Differential Revision: D34744977

fbshipit-source-id: 625a0df43761894d13a01bc1779576fc3f29bf6f
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@jspark1105 @facebook-github-bot
jspark1105 authored and facebook-github-bot committed Mar 9, 2022
1 parent 1baf483 commit 4dfc2a7
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Showing 20 changed files with 273 additions and 291 deletions.
4 changes: 2 additions & 2 deletions fbgemm_gpu/codegen/embedding_backward_split_cpu_approx_template.cpp
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Expand Up @@ -192,12 +192,12 @@ split_embedding_backward_codegen_{{ optimizer }}_cpu(
{% endif %}

AT_DISPATCH_FLOATING_TYPES_AND_HALF(
grad_output.scalar_type(), "split_embedding_backward_cpu", [&]() {
grad_output.scalar_type(), "split_embedding_backward_cpu", [&] {
using grad_t = scalar_t;
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
host_weights.scalar_type(),
"split_embedding_backward_cpu_inner",
[&]() {
[&] {
split_embedding_backward_approx_cpu_kernel<scalar_t, grad_t>(
grad_output,
host_weights,
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4 changes: 2 additions & 2 deletions fbgemm_gpu/codegen/embedding_backward_split_cpu_template.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -345,7 +345,7 @@ void split_embedding_backward_exact_cpu_dense_kernel(
grad_output = grad_output.contiguous();

AT_DISPATCH_FLOATING_TYPES_AND_HALF(
host_weights.scalar_type(), "split_embedding_backward_exact_cpu", [&]() {
host_weights.scalar_type(), "split_embedding_backward_exact_cpu", [&] {
// TODO: respect output_dtype
using grad_t = float;
split_embedding_backward_exact_cpu_kernel<scalar_t, grad_t>(
Expand Down Expand Up @@ -377,7 +377,7 @@ void split_embedding_backward_exact_cpu_dense_kernel(
// When input is dense enough, avoid sorting and just treat as dense.
auto grad = zeros_like(host_weights, grad_output.dtype());
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
grad_output.scalar_type(), "split_embedding_backward_exact_cpu", [&]() {
grad_output.scalar_type(), "split_embedding_backward_exact_cpu", [&] {

split_embedding_backward_exact_cpu_dense_kernel<scalar_t>(
grad,
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4 changes: 2 additions & 2 deletions fbgemm_gpu/codegen/embedding_backward_split_indice_weights_template.cu
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Expand Up @@ -229,7 +229,7 @@ Tensor {{ "dense" if dense else "split" }}_embedding_codegen_grad_indice_weights
lxu_cache_weights.type(),
{% endif %}
"split_embedding_codegen_grad_indice_weights_kernel",
([&] {
[&] {
{% for kMaxVecsPerThread in range(1, max_embedding_dim // 128 + 1) %}
if (max_D <= {{ 128 * kMaxVecsPerThread }}) {
{{ "dense" if dense else "split" }}_embedding_codegen_grad_indice_weights_kernel<
Expand Down Expand Up @@ -279,7 +279,7 @@ Tensor {{ "dense" if dense else "split" }}_embedding_codegen_grad_indice_weights
return;
}
{% endfor %}
}));
});
C10_CUDA_KERNEL_LAUNCH_CHECK();
return grad_indice_weights;
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4 changes: 2 additions & 2 deletions fbgemm_gpu/codegen/embedding_backward_split_template.cu
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Expand Up @@ -837,7 +837,7 @@ split_embedding{{ "_nobag" if nobag else "" }}_backward_codegen_{{ optimizer }}_
dev_weights.type(),
{% endif %}
"split_embedding_backward_{{ optimizer }}_exact_kernel",
([&] {
[&] {
{% if weighted %}
auto indice_weights_sorted = at::empty_like(indice_weights);
{
Expand Down Expand Up @@ -1133,7 +1133,7 @@ split_embedding{{ "_nobag" if nobag else "" }}_backward_codegen_{{ optimizer }}_
return;
}
{% endfor %}
}));
});
return {{ "grad_dev_weights" if dense else "" }};
}
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2 changes: 1 addition & 1 deletion fbgemm_gpu/codegen/embedding_bounds_check.cu
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Expand Up @@ -130,7 +130,7 @@ void bounds_check_indices_cuda(
}
constexpr size_t kNumThreads = 256;

AT_DISPATCH_INDEX_TYPES(indices.scalar_type(), "bounds_check_indices", [&]() {
AT_DISPATCH_INDEX_TYPES(indices.scalar_type(), "bounds_check_indices", [&] {
bounds_check_indices_kernel<index_t>
<<<div_round_up(B * T, kNumThreads / fbgemm_gpu::kWarpSize),
dim3(fbgemm_gpu::kWarpSize, kNumThreads / fbgemm_gpu::kWarpSize),
Expand Down
2 changes: 1 addition & 1 deletion fbgemm_gpu/codegen/embedding_bounds_check_host_cpu.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ void bounds_check_indices_cpu(
const auto rows_per_table_acc = rows_per_table.accessor<int64_t, 1>();
auto warning_acc = warning.data_ptr<int64_t>();

AT_DISPATCH_INDEX_TYPES(indices.scalar_type(), "bounds_check_indices", [&]() {
AT_DISPATCH_INDEX_TYPES(indices.scalar_type(), "bounds_check_indices", [&] {
auto offsets_acc = offsets.accessor<index_t, 1>();
auto indices_acc = indices.accessor<index_t, 1>();
auto num_indices = indices.numel();
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6 changes: 3 additions & 3 deletions fbgemm_gpu/codegen/embedding_forward_quantized_cpu_template.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -164,13 +164,13 @@ Tensor int_nbit_split_embedding_codegen_forward_{{ wdesc }}_cpu(

const auto* weights_tys_acc = weights_tys.data_ptr<uint8_t>();

DISPATCH_OUTPUT_TYPES(output.type(), "intn_split_embedding_codegen_forward_kernel", ([&] {
DISPATCH_OUTPUT_TYPES(output.type(), "intn_split_embedding_codegen_forward_kernel", [&] {
auto* output_acc = output.data_ptr<output_t>();
{% if weighted %}
const float* indice_weights_acc = indice_weights.data_ptr<float>();
{% endif %}

AT_DISPATCH_INDEX_TYPES(indices.scalar_type(), "int_nbit_split_embedding_codegen_forward_", [&] () {
AT_DISPATCH_INDEX_TYPES(indices.scalar_type(), "int_nbit_split_embedding_codegen_forward_", [&] {
const auto* indices_acc = indices.data_ptr<index_t>();
const auto* offsets_acc = offsets.data_ptr<index_t>();
const auto* D_offsets_acc = D_offsets.data_ptr<int32_t>();
Expand Down Expand Up @@ -320,7 +320,7 @@ Tensor int_nbit_split_embedding_codegen_forward_{{ wdesc }}_cpu(
}
return;
});
}));
});
return output;
}

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8 changes: 4 additions & 4 deletions fbgemm_gpu/codegen/embedding_forward_split_cpu.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -195,14 +195,14 @@ Tensor split_embedding_codegen_forward_cpu(
TORCH_CHECK(
!indice_weights.defined() || indice_weights.scalar_type() != at::kHalf);
AT_DISPATCH_FLOATING_TYPES(
output.scalar_type(), "split_embedding_cpu_forward", [&]() {
output.scalar_type(), "split_embedding_cpu_forward", [&] {
using output_t = scalar_t;
AT_DISPATCH_FLOATING_TYPES_AND2(
at::ScalarType::Half,
at::ScalarType::Byte,
weights.scalar_type(),
"split_embedding_cpu_forward",
[&]() {
[&] {
using ind_weights_t = std::conditional<
std::is_same<scalar_t, double>::value,
double,
Expand Down Expand Up @@ -294,12 +294,12 @@ Tensor split_embedding_codegen_grad_indice_weights_cpu(
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
grad_output.scalar_type(),
"split_embedding_grad_indice_weights_cpu_outer",
[&]() {
[&] {
using grad_t = scalar_t;
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
weights.scalar_type(),
"split_embedding_grad_indice_weights_cpu",
[&]() {
[&] {
using weights_t = scalar_t;
split_embedding_grad_indice_weights_cpu_kernel<weights_t, grad_t>(
grad_output,
Expand Down
4 changes: 2 additions & 2 deletions fbgemm_gpu/codegen/embedding_forward_split_template.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -385,7 +385,7 @@ Tensor {{ "dense" if dense else "split" }}_embedding{{ "_nobag" if nobag else ""
lxu_cache_weights.type(),
output.type(),
{% endif %}
"batched_embedding{{ "_nobag" if nobag else "" }}_forward_kernel_2", ([&] {
"batched_embedding{{ "_nobag" if nobag else "" }}_forward_kernel_2", [&] {
{% if not nobag %}
{% for kMaxVecsPerThread in range(1, max_embedding_dim // 128 + 1) %}
if (max_D <= {{ 128 * kMaxVecsPerThread }}) {
Expand Down Expand Up @@ -467,7 +467,7 @@ Tensor {{ "dense" if dense else "split" }}_embedding{{ "_nobag" if nobag else ""
return;
{% endif %}
}));
});
C10_CUDA_KERNEL_LAUNCH_CHECK();
return output;
Expand Down
18 changes: 9 additions & 9 deletions fbgemm_gpu/src/histogram_binning_calibration_ops.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -76,7 +76,7 @@ std::tuple<Tensor, Tensor> histogram_binning_calibration_cuda(
const auto bin_num_examples_packed = bin_num_examples.contiguous();
const auto bin_num_positives_packed = bin_num_positives.contiguous();
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
logit.type(), "histogram_binning_calibration_cuda", [&]() {
logit.type(), "histogram_binning_calibration_cuda", [&] {
histogram_binning_calibration_kernel<scalar_t>
<<<fbgemm_gpu::div_round_up(logit.numel(), num_threads),
num_threads,
Expand Down Expand Up @@ -201,10 +201,10 @@ std::tuple<Tensor, Tensor> histogram_binning_calibration_by_feature_cuda(
AT_DISPATCH_INDEX_TYPES(
segment_offsets.scalar_type(),
"to_dense_segment_value_cuda_wrapper",
[&]() {
[&] {
using offset_t = index_t;
AT_DISPATCH_INDEX_TYPES(
segment_value.scalar_type(), "to_dense_segment_value_cuda", [&]() {
segment_value.scalar_type(), "to_dense_segment_value_cuda", [&] {
using value_t = index_t;
to_dense_segment_value_kernel<offset_t, value_t>
<<<fbgemm_gpu::div_round_up(
Expand Down Expand Up @@ -232,12 +232,12 @@ std::tuple<Tensor, Tensor> histogram_binning_calibration_by_feature_cuda(
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
logit.type(),
"histogram_binning_calibration_by_feature_cuda_wrapper",
[&]() {
[&] {
using logit_t = scalar_t;
AT_DISPATCH_INDEX_TYPES(
dense_segment_value_packed.scalar_type(),
"histogram_binning_calibration_by_feature_cuda",
[&]() {
[&] {
using segment_value_t = index_t;
histogram_binning_calibration_by_feature_kernel<
logit_t,
Expand Down Expand Up @@ -362,10 +362,10 @@ generic_histogram_binning_calibration_by_feature_cuda(
AT_DISPATCH_INDEX_TYPES(
segment_offsets.scalar_type(),
"to_dense_segment_value_cuda_wrapper",
[&]() {
[&] {
using offset_t = index_t;
AT_DISPATCH_INDEX_TYPES(
segment_value.scalar_type(), "to_dense_segment_value_cuda", [&]() {
segment_value.scalar_type(), "to_dense_segment_value_cuda", [&] {
using value_t = index_t;
to_dense_segment_value_kernel<offset_t, value_t>
<<<fbgemm_gpu::div_round_up(
Expand All @@ -392,12 +392,12 @@ generic_histogram_binning_calibration_by_feature_cuda(
AT_DISPATCH_FLOATING_TYPES_AND_HALF(
logit.type(),
"generic_histogram_binning_calibration_by_feature_cuda_wrapper",
[&]() {
[&] {
using logit_t = scalar_t;
AT_DISPATCH_INDEX_TYPES(
dense_segment_value_packed.scalar_type(),
"generic_histogram_binning_calibration_by_feature_cuda",
[&]() {
[&] {
using segment_value_t = index_t;
generic_histogram_binning_calibration_by_feature_kernel<
logit_t,
Expand Down
4 changes: 2 additions & 2 deletions fbgemm_gpu/src/input_combine_cpu.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ Tensor _cat_int_tensors(

for (size_t i = 0; i < tensor_list.size(); i++) {
AT_DISPATCH_INDEX_TYPES(
tensor_list[i].scalar_type(), "tbe_cat_inputs_", [&]() {
tensor_list[i].scalar_type(), "tbe_cat_inputs_", [&] {
auto indices_acc = tensor_list[i].accessor<index_t, 1>();
for (auto j = 0; j < tensor_list[i].numel(); j++) {
combined_tensors_acc[idx++] = static_cast<int32_t>(indices_acc[j]);
Expand Down Expand Up @@ -135,7 +135,7 @@ std::tuple<Tensor, Tensor, Tensor> tbe_input_combine_cpu(

for (size_t i = 0; i < offsets_list.size(); i++) {
AT_DISPATCH_INDEX_TYPES(
offsets_list[i].scalar_type(), "tbe_input_offsets_", [&]() {
offsets_list[i].scalar_type(), "tbe_input_offsets_", [&] {
auto offsets_acc = offsets_list[i].accessor<index_t, 1>();
for (int64_t j = 1,
size = offsets_list[i].numel() -
Expand Down
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