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Fix common typos and misspellings (#164413)

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Summary:
This commit fixes numerous typos and misspellings found throughout the codebase. The fixes improve code readability and documentation consistency across C++, Python, CUDA, and documentation files.

## Typos Fixed

| Before | After | Occurrences |
|--------|-------|-------------|
| occured | occurred | 14 |
| accross | across | 9 |
| lenght/lenghts | length/lengths | 8 |
| unneccessary | unnecessary | 5 |
| Peform | Perform | 4 |
| furture | future | 3 |
| paritioned | partitioned | 2 |
| desireable | desirable | 2 |
| registerations | registrations | 2 |
| seperated | separated | 2 |
| intialized | initialized | 2 |
| capatibility | compatibility | 2 |
| peformed | performed | 2 |
| Exmple | Example | 2 |
| comma_seperated | comma_separated | 2 |
| cumsuming | consuming | 2 |
| neccessary | necessary | 1 |
| ParamterMetadataTable | ParameterMetadataTable | 1 |
| matached | matched | 1 |
| conaitner | container | 1 |
| reivew | review | 1 |
| prioriry | priority | 1 |
| Alocated | Allocated | 1 |
| opportunixtically | opportunistically | 1 |
| peformance | performance | 1 |
| equavalent | equivalent | 1 |
| asssumed | assumed | 1 |
| valdiation | validation | 1 |
| apprear | appear | 1 |
| consectuve | consecutive | 1 |
| dependending | depending | 1 |
| copnversion | conversion | 1 |
| weigted | weighted | 1 |
| repreesenting | representing | 1 |
| finialize | finalize | 1 |
| unintialized | uninitialized | 1 |
| conbined | combined | 1 |
| tesnor | tensor | 1 |
| desugared | discarded | 1 |
| behaviour | behavior | 1 |
| paramerizaitons | parametrizations | 1 |
| compute_output_lenghths_kernel | compute_output_lengths_kernel | 1 |

Test Plan: N/A - mostly comments - waiting on CI

Differential Revision: D83695665

Pull Request resolved: https://github.com/pytorch/pytorch/pull/164413
Approved by: https://github.com/eqy, https://github.com/larryliu0820
This commit is contained in:
Pierre Moulon 2025-10-03 23:19:41 +00:00 committed by PyTorch MergeBot
parent 3ddf2018d0
commit b6b7a44dec
5 changed files with 14 additions and 14 deletions
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10
aten/src/ATen/cpu/vec/vec256/vec256_int.h
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@ -905,7 +905,7 @@ class Vectorized8 : public Vectorizedi {
// Because loadu(const void* ptr, T count) requires zero initialization for
// upper 128 bits. However, by using _mm256_castsi128_si256, the upper 128
// bits of the result are undefined.
// TODO<leslie> We can use _mm256_zextsi128_si256 in the furture,
// TODO<leslie> We can use _mm256_zextsi128_si256 in the future,
// since gcc 9.3 doesn't support it now.
__m128i input_128 = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(ptr));
return _mm256_castsi128_si256(input_128);
@ -1844,7 +1844,7 @@ Vectorized<int16_t> inline shift_256_16(
c0 = _mm256_srav_epi32(a0, b0);
c0 = _mm256_shuffle_epi8(c0, ctl_1_0);
// Peform shifting the same way for input array elements with
// Perform shifting the same way for input array elements with
// idx%2==1.
__m256i a1 = _mm256_and_si256(a, keep_1);
__m256i b1 = _mm256_shuffle_epi8(b, ctl_1_0);
@ -2180,7 +2180,7 @@ Vectorized<T> inline shift_256_8(
c0 = _mm256_srlv_epi32(a0, b0);
c0 = _mm256_shuffle_epi8(c0, ctl_3_0);
// Peform shifting the same way for input array elements with
// Perform shifting the same way for input array elements with
// idx%4==1.
__m256i a1 = _mm256_shuffle_epi8(a, ctl_1_3);
__m256i b1 = _mm256_shuffle_epi8(b, ctl_1_0);
@ -2193,7 +2193,7 @@ Vectorized<T> inline shift_256_8(
c1 = _mm256_srlv_epi32(a1, b1);
c1 = _mm256_shuffle_epi8(c1, ctl_3_1);
// Peform shifting the same way for input array elements with
// Perform shifting the same way for input array elements with
// idx%4==2.
__m256i a2 = _mm256_shuffle_epi8(a, ctl_2_3);
__m256i b2 = _mm256_shuffle_epi8(b, ctl_2_0);
@ -2206,7 +2206,7 @@ Vectorized<T> inline shift_256_8(
c2 = _mm256_srlv_epi32(a2, b2);
c2 = _mm256_shuffle_epi8(c2, ctl_3_2);
// Peform shifting the same way for input array elements with
// Perform shifting the same way for input array elements with
// idx%4==3.
__m256i a3 = _mm256_and_si256(a, keep_3);
__m256i b3 = _mm256_shuffle_epi8(b, ctl_3_0);

4
aten/src/ATen/cpu/vec/vec512/vec512_int.h
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@ -1088,7 +1088,7 @@ class Vectorized8 : public Vectorizedi {
// Because loadu(const void* ptr, T count) requires zero initialization for
// upper 384 bits. However, by using _mm512_castsi128_si512, the upper 384
// bits of the result are undefined.
// TODO<leslie> We can use _mm512_zextsi128_si512 in the furture,
// TODO<leslie> We can use _mm512_zextsi128_si512 in the future,
// since gcc 9.3 doesn't support it now.
__m128i input_128 = _mm_loadu_si128(reinterpret_cast<const __m128i*>(ptr));
return _mm512_castsi128_si512(input_128);
@ -2022,7 +2022,7 @@ Vectorized<T> inline shift_512_8(
c0 = _mm512_srlv_epi16(a0, b0);
c0 = _mm512_shuffle_epi8(c0, ctl_1_0);
// Peform shifting the same way for input array elements with
// Perform shifting the same way for input array elements with
// idx%2==1.
__m512i a1 = _mm512_and_si512(a, keep_1);
__m512i b1 = _mm512_shuffle_epi8(b, ctl_1_0);

2
aten/src/ATen/native/cudnn/MHA.cpp
View File

@ -1379,7 +1379,7 @@ void run_cudnn_SDP_fprop(
cudnnHandle_t handle = getCudnnHandle();
// NB: The key initialization will round up sequence length, stride data etc.
// if use_ragged_in_dense is enabled (to allow multiple sequence lenghths to
// if use_ragged_in_dense is enabled (to allow multiple sequence lengths to
// reuse the same cached value/graph)
auto key = MHACacheKeyWrapper(
b,

2
test/mobile/test_lite_script_module.py
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@ -437,7 +437,7 @@ class TestLiteScriptModule(TestCase):
# additional context to the exception message and preserve the correct
# C++ stack trace for symbolication. i.e. it isn't possible to add
# the debug handle string to show where in the Python code the exception
# occured w/o first changing
# occurred w/o first changing
# torch::jit::JITException to extend c10::Error.
self.assertTrue("self.val and val are same" in error_message)

10
torch/export/exported_program.py
View File

@ -532,16 +532,16 @@ def _decompose_and_get_gm_with_new_signature_constants(
_verify_stack_trace(gm)
_verify_placeholder_names(gm, new_graph_signature)
gm, new_graph_signature = _remove_unneccessary_copy_op_pass(
gm, new_graph_signature = _remove_unnecessary_copy_op_pass(
gm, new_graph_signature
)
# When we apply parameterixzation rule to unwrap
# When we apply parameterization rule to unwrap
# subclasses, the state dict will now have different
# desugared parameters. We need to manually filter those
# and update the ep.state_dict. Ideally, we should just return
# the state dict of ep.module but ep.module only stores params
# buffers that participate in forward. If we undo this behaviour,
# buffers that participate in forward. If we undo this behavior,
# it would break some downstream users.
new_state_dict = {
**ep.state_dict,
@ -781,7 +781,7 @@ def _decompose_and_get_gm_with_new_signature_constants(
return gm, new_graph_signature, ep.state_dict
def _remove_unneccessary_copy_op_pass(
def _remove_unnecessary_copy_op_pass(
gm: torch.fx.GraphModule, new_graph_signature: ExportGraphSignature
) -> tuple[torch.fx.GraphModule, ExportGraphSignature]:
"""
@ -894,7 +894,7 @@ def _get_updated_module_call_graph(
user_input_counter += 1
# For all the parameters and buffers, we first see
# if they are result of paramerizaitons and if they
# if they are result of parametrizations and if they
# are, we log them and error later
old_param_to_desugared = defaultdict(list)
for name, target in new_graph_params_buffers.items():