You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
(mlenv) C:\Users\Admin\nanoGPT>python train.py config/train_shakespeare_char.py
Overriding config with config/train_shakespeare_char.py:
train a miniature character-level shakespeare model
good for debugging and playing on macbooks and such
out_dir = 'out-shakespeare-char'
eval_interval = 250 # keep frequent because we'll overfit
eval_iters = 200
log_interval = 10 # don't print too too often
we expect to overfit on this small dataset, so only save when val improves
always_save_checkpoint = False
wandb_log = False # override via command line if you like
wandb_project = 'shakespeare-char'
wandb_run_name = 'mini-gpt'
dataset = 'shakespeare_char'
gradient_accumulation_steps = 1
batch_size = 64
block_size = 256 # context of up to 256 previous characters
baby GPT model :)
n_layer = 6
n_head = 6
n_embd = 384
dropout = 0.2
learning_rate = 1e-3 # with baby networks can afford to go a bit higher
max_iters = 5000
lr_decay_iters = 5000 # make equal to max_iters usually
min_lr = 1e-4 # learning_rate / 10 usually
beta2 = 0.99 # make a bit bigger because number of tokens per iter is small
warmup_iters = 100 # not super necessary potentially
on macbook also add
device = 'cpu' # run on cpu only
compile = False # do not torch compile the model
tokens per iteration will be: 16,384
found vocab_size = 65 (inside data\shakespeare_char\meta.pkl)
Initializing a new model from scratch
number of parameters: 10.65M
C:\Users\Admin\nanoGPT\train.py:196: FutureWarning: torch.cuda.amp.GradScaler(args...) is deprecated. Please use torch.amp.GradScaler('cuda', args...) instead.
scaler = torch.cuda.amp.GradScaler(enabled=(dtype == 'float16'))
num decayed parameter tensors: 26, with 10,740,096 parameters
num non-decayed parameter tensors: 13, with 4,992 parameters
using fused AdamW: True
compiling the model... (takes a ~minute)
C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py:1903: UserWarning: 1Torch was not compiled with flash attention. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\transformers\cuda\sdp_utils.cpp:555.)
return node.target(*args, **kwargs)
Traceback (most recent call last):
File "C:\Users\Admin\nanoGPT\train.py", line 264, in
losses = estimate_loss()
^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\nanoGPT\train.py", line 224, in estimate_loss
logits, loss = model(X, Y)
^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\eval_frame.py", line 433, in _fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 1116, in call
return self._torchdynamo_orig_callable(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 948, in call
result = self._inner_convert(
^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 472, in call
return _compile(
^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_utils_internal.py", line 84, in wrapper_function
return StrobelightCompileTimeProfiler.profile_compile_time(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_strobelight\compile_time_profiler.py", line 129, in profile_compile_time
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 817, in _compile
guarded_code = compile_inner(code, one_graph, hooks, transform)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py", line 231, in time_wrapper
r = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 636, in compile_inner
out_code = transform_code_object(code, transform)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\bytecode_transformation.py", line 1185, in transform_code_object
transformations(instructions, code_options)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 178, in fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 582, in transform
tracer.run()
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 2451, in run
super().run()
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 893, in run
while self.step():
^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 805, in step
self.dispatch_table[inst.opcode](self, inst)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 2642, in RETURN_VALUE
self.return(inst)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 2627, in return
self.output.compile_subgraph(
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\output_graph.py", line 1123, in compile_subgraph
self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\output_graph.py", line 1318, in compile_and_call_fx_graph
compiled_fn = self.call_user_compiler(gm)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py", line 231, in time_wrapper
r = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\output_graph.py", line 1409, in call_user_compiler
raise BackendCompilerFailed(self.compiler_fn, e).with_traceback(
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\output_graph.py", line 1390, in call_user_compiler
compiled_fn = compiler_fn(gm, self.example_inputs())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\repro\after_dynamo.py", line 129, in call
compiled_gm = compiler_fn(gm, example_inputs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_init.py", line 1951, in call
return compile_fx(model, inputs, config_patches=self.config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\compile_fx.py", line 1505, in compile_fx
return aot_autograd(
^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\backends\common.py", line 69, in call
cg = aot_module_simplified(gm, example_inputs, **self.kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_functorch\aot_autograd.py", line 954, in aot_module_simplified
compiled_fn, _ = create_aot_dispatcher_function(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py", line 231, in time_wrapper
r = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_functorch\aot_autograd.py", line 687, in create_aot_dispatcher_function
compiled_fn, fw_metadata = compiler_fn(
^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_functorch_aot_autograd\jit_compile_runtime_wrappers.py", line 168, in aot_dispatch_base
compiled_fw = compiler(fw_module, updated_flat_args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py", line 231, in time_wrapper
r = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\compile_fx.py", line 1352, in fw_compiler_base
_recursive_joint_graph_passes(model)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\compile_fx.py", line 256, in _recursive_joint_graph_passes
joint_graph_passes(gm)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\fx_passes\joint_graph.py", line 326, in joint_graph_passes
count += patterns.apply(graph.graph) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\pattern_matcher.py", line 1698, in apply
if is_match(m) and entry.extra_check(m):
^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\pattern_matcher.py", line 1314, in check_fn
if is_match(specific_pattern_match) and extra_check(specific_pattern_match):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\fx_passes\pad_mm.py", line 502, in should_pad_mm
return should_pad_common(mat1, mat2) and should_pad_bench(
^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\fx_passes\pad_mm.py", line 492, in should_pad_bench
set_cached_should_pad(key, should_pad)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\fx_passes\pad_mm.py", line 237, in set_cached_should_pad
return get_pad_cache().set_value(key, value=value)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\codecache.py", line 230, in set_value
self.update_local_cache(cache)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\codecache.py", line 201, in update_local_cache
write_atomic(
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\codecache.py", line 404, in write_atomic
tmp_path.rename(path)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\pathlib.py", line 1175, in rename
os.rename(self, target)
torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
FileExistsError: [WinError 183] Cannot create a file when that file already exists: 'C:\Users\Admin\AppData\Local\Temp\torchinductor_Admin\cache\.13268.32284.tmp' -> 'C:\Users\Admin\AppData\Local\Temp\torchinductor_Admin\cache\e2263ba6e33073368c52f4aa78f67071b5f51eedea3cc454388bc54a5d4af969'
Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information
You can suppress this exception and fall back to eager by setting:
import torch._dynamo
torch._dynamo.config.suppress_errors = True
The text was updated successfully, but these errors were encountered:
Can someone help on this issue?
(mlenv) C:\Users\Admin\nanoGPT>python train.py config/train_shakespeare_char.py
Overriding config with config/train_shakespeare_char.py:
train a miniature character-level shakespeare model
good for debugging and playing on macbooks and such
out_dir = 'out-shakespeare-char'
eval_interval = 250 # keep frequent because we'll overfit
eval_iters = 200
log_interval = 10 # don't print too too often
we expect to overfit on this small dataset, so only save when val improves
always_save_checkpoint = False
wandb_log = False # override via command line if you like
wandb_project = 'shakespeare-char'
wandb_run_name = 'mini-gpt'
dataset = 'shakespeare_char'
gradient_accumulation_steps = 1
batch_size = 64
block_size = 256 # context of up to 256 previous characters
baby GPT model :)
n_layer = 6
n_head = 6
n_embd = 384
dropout = 0.2
learning_rate = 1e-3 # with baby networks can afford to go a bit higher
max_iters = 5000
lr_decay_iters = 5000 # make equal to max_iters usually
min_lr = 1e-4 # learning_rate / 10 usually
beta2 = 0.99 # make a bit bigger because number of tokens per iter is small
warmup_iters = 100 # not super necessary potentially
on macbook also add
device = 'cpu' # run on cpu only
compile = False # do not torch compile the model
tokens per iteration will be: 16,384
found vocab_size = 65 (inside data\shakespeare_char\meta.pkl)
Initializing a new model from scratch
number of parameters: 10.65M
C:\Users\Admin\nanoGPT\train.py:196: FutureWarning:
torch.cuda.amp.GradScaler(args...)
is deprecated. Please usetorch.amp.GradScaler('cuda', args...)
instead.scaler = torch.cuda.amp.GradScaler(enabled=(dtype == 'float16'))
num decayed parameter tensors: 26, with 10,740,096 parameters
num non-decayed parameter tensors: 13, with 4,992 parameters
using fused AdamW: True
compiling the model... (takes a ~minute)
C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py:1903: UserWarning: 1Torch was not compiled with flash attention. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\transformers\cuda\sdp_utils.cpp:555.)
return node.target(*args, **kwargs)
Traceback (most recent call last):
File "C:\Users\Admin\nanoGPT\train.py", line 264, in
losses = estimate_loss()
^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\nanoGPT\train.py", line 224, in estimate_loss
logits, loss = model(X, Y)
^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\eval_frame.py", line 433, in _fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 1116, in call
return self._torchdynamo_orig_callable(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 948, in call
result = self._inner_convert(
^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 472, in call
return _compile(
^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_utils_internal.py", line 84, in wrapper_function
return StrobelightCompileTimeProfiler.profile_compile_time(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_strobelight\compile_time_profiler.py", line 129, in profile_compile_time
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 817, in _compile
guarded_code = compile_inner(code, one_graph, hooks, transform)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py", line 231, in time_wrapper
r = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 636, in compile_inner
out_code = transform_code_object(code, transform)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\bytecode_transformation.py", line 1185, in transform_code_object
transformations(instructions, code_options)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 178, in fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\convert_frame.py", line 582, in transform
tracer.run()
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 2451, in run
super().run()
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 893, in run
while self.step():
^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 805, in step
self.dispatch_table[inst.opcode](self, inst)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 2642, in RETURN_VALUE
self.return(inst)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\symbolic_convert.py", line 2627, in return
self.output.compile_subgraph(
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\output_graph.py", line 1123, in compile_subgraph
self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\output_graph.py", line 1318, in compile_and_call_fx_graph
compiled_fn = self.call_user_compiler(gm)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py", line 231, in time_wrapper
r = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\output_graph.py", line 1409, in call_user_compiler
raise BackendCompilerFailed(self.compiler_fn, e).with_traceback(
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\output_graph.py", line 1390, in call_user_compiler
compiled_fn = compiler_fn(gm, self.example_inputs())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\repro\after_dynamo.py", line 129, in call
compiled_gm = compiler_fn(gm, example_inputs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_init.py", line 1951, in call
return compile_fx(model, inputs, config_patches=self.config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\compile_fx.py", line 1505, in compile_fx
return aot_autograd(
^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\backends\common.py", line 69, in call
cg = aot_module_simplified(gm, example_inputs, **self.kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_functorch\aot_autograd.py", line 954, in aot_module_simplified
compiled_fn, _ = create_aot_dispatcher_function(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py", line 231, in time_wrapper
r = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_functorch\aot_autograd.py", line 687, in create_aot_dispatcher_function
compiled_fn, fw_metadata = compiler_fn(
^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_functorch_aot_autograd\jit_compile_runtime_wrappers.py", line 168, in aot_dispatch_base
compiled_fw = compiler(fw_module, updated_flat_args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_dynamo\utils.py", line 231, in time_wrapper
r = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\compile_fx.py", line 1352, in fw_compiler_base
_recursive_joint_graph_passes(model)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\compile_fx.py", line 256, in _recursive_joint_graph_passes
joint_graph_passes(gm)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\fx_passes\joint_graph.py", line 326, in joint_graph_passes
count += patterns.apply(graph.graph) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\pattern_matcher.py", line 1698, in apply
if is_match(m) and entry.extra_check(m):
^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\pattern_matcher.py", line 1314, in check_fn
if is_match(specific_pattern_match) and extra_check(specific_pattern_match):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\fx_passes\pad_mm.py", line 502, in should_pad_mm
return should_pad_common(mat1, mat2) and should_pad_bench(
^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\fx_passes\pad_mm.py", line 492, in should_pad_bench
set_cached_should_pad(key, should_pad)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\fx_passes\pad_mm.py", line 237, in set_cached_should_pad
return get_pad_cache().set_value(key, value=value)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\codecache.py", line 230, in set_value
self.update_local_cache(cache)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\codecache.py", line 201, in update_local_cache
write_atomic(
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\site-packages\torch_inductor\codecache.py", line 404, in write_atomic
tmp_path.rename(path)
File "C:\Users\Admin\anaconda3\envs\mlenv\Lib\pathlib.py", line 1175, in rename
os.rename(self, target)
torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
FileExistsError: [WinError 183] Cannot create a file when that file already exists: 'C:\Users\Admin\AppData\Local\Temp\torchinductor_Admin\cache\.13268.32284.tmp' -> 'C:\Users\Admin\AppData\Local\Temp\torchinductor_Admin\cache\e2263ba6e33073368c52f4aa78f67071b5f51eedea3cc454388bc54a5d4af969'
Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information
You can suppress this exception and fall back to eager by setting:
import torch._dynamo
torch._dynamo.config.suppress_errors = True
The text was updated successfully, but these errors were encountered: