chore: linter fixes by black

docs/_downloads/0e30a6276601af7e5fc4d5166e2e3d37/torch_compile_advanced_usage.py

@@ -4,7 +4,8 @@
 Torch Compile Advanced Usage
 ======================================================
 
-This interactive script is intended as an overview of the process by which `torch_tensorrt.compile(..., ir="torch_compile", ...)` works, and how it integrates with the `torch.compile` API."""
+This interactive script is intended as an overview of the process by which `torch_tensorrt.compile(..., ir="torch_compile", ...)` works, and how it integrates with the `torch.compile` API.
+"""
 
 # %%
 # Imports and Model Definition

docs/_downloads/2a9ac10f2667047a7f398d1593b7ca33/torch_export_gpt2.py

@@ -4,7 +4,8 @@
 Compiling GPT2 using the dynamo backend
 ==========================================================
 
-This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model."""
+This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model.
+"""
 
 # %%
 # Imports and Model Definition

docs/_downloads/3d4d74f6636d986f33167154f6553961/torch_export_cudagraphs.py

@@ -4,7 +4,8 @@
 Torch Export with Cudagraphs
 ======================================================
 
-This interactive script is intended as an overview of the process by which the Torch-TensorRT Cudagraphs integration can be used in the `ir="dynamo"` path. The functionality works similarly in the `torch.compile` path as well."""
+This interactive script is intended as an overview of the process by which the Torch-TensorRT Cudagraphs integration can be used in the `ir="dynamo"` path. The functionality works similarly in the `torch.compile` path as well.
+"""
 
 # %%
 # Imports and Model Definition

docs/_downloads/418941399c146271a7b7728ba3059960/dynamo_compile_resnet_example.py

@@ -4,7 +4,8 @@
 Compiling ResNet using the Torch-TensorRT Dyanmo Frontend
 ==========================================================
 
-This interactive script is intended as a sample of the `torch_tensorrt.dynamo.compile` workflow on a ResNet model."""
+This interactive script is intended as a sample of the `torch_tensorrt.dynamo.compile` workflow on a ResNet model.
+"""
 
 # %%
 # Imports and Model Definition

docs/_downloads/7b7004dc2ea6f839be532665e16e0426/torch_export_llama2.py

@@ -4,7 +4,8 @@
 Compiling Llama2 using the dynamo backend
 ==========================================================
 
-This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model."""
+This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model.
+"""
 
 # %%
 # Imports and Model Definition

docs/_downloads/d6e1bb6ec5f884994554d9d12e37a0f6/torch_compile_resnet_example.py

@@ -4,7 +4,8 @@
 Compiling ResNet with dynamic shapes using the `torch.compile` backend
 ==========================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a ResNet model."""
+This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a ResNet model.
+"""
 
 # %%
 # Imports and Model Definition

docs/_downloads/dfa60e8f9850fd7761f3e7da81304d32/torch_compile_transformers_example.py

@@ -4,7 +4,8 @@
 Compiling BERT using the `torch.compile` backend
 ==============================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a BERT model."""
+This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a BERT model.
+"""
 
 # %%
 # Imports and Model Definition

docs/_downloads/e1ef5a42560a98a132f56a79d0b66f79/dynamo_compile_advanced_usage.py

@@ -4,7 +4,8 @@
 Dynamo Compile Advanced Usage
 ======================================================
 
-This interactive script is intended as an overview of the process by which `torch_tensorrt.dynamo.compile` works, and how it integrates with the new `torch.compile` API."""
+This interactive script is intended as an overview of the process by which `torch_tensorrt.dynamo.compile` works, and how it integrates with the new `torch.compile` API.
+"""
 
 # %%
 # Imports and Model Definition

docs/_downloads/e550c5f53cc43e11aa6da8cfb79b54df/dynamo_compile_transformers_example.py

@@ -4,7 +4,8 @@
 Compiling a Transformer using torch.compile and TensorRT
 ==============================================================
 
-This interactive script is intended as a sample of the `torch_tensorrt.dynamo.compile` workflow on a transformer-based model."""
+This interactive script is intended as a sample of the `torch_tensorrt.dynamo.compile` workflow on a transformer-based model.
+"""
 
 # %%
 # Imports and Model Definition

docs/v1.4.0/_downloads/418941399c146271a7b7728ba3059960/dynamo_compile_resnet_example.py

@@ -4,7 +4,8 @@
 Compiling ResNet using the Torch-TensorRT Dyanmo Frontend
 ==========================================================
 
-This interactive script is intended as a sample of the `torch_tensorrt.dynamo.compile` workflow on a ResNet model."""
+This interactive script is intended as a sample of the `torch_tensorrt.dynamo.compile` workflow on a ResNet model.
+"""
 
 # %%
 # Imports and Model Definition

docs/v1.4.0/_downloads/e1ef5a42560a98a132f56a79d0b66f79/dynamo_compile_advanced_usage.py

@@ -4,7 +4,8 @@
 Dynamo Compile Advanced Usage
 ======================================================
 
-This interactive script is intended as an overview of the process by which `torch_tensorrt.dynamo.compile` works, and how it integrates with the new `torch.compile` API."""
+This interactive script is intended as an overview of the process by which `torch_tensorrt.dynamo.compile` works, and how it integrates with the new `torch.compile` API.
+"""
 
 # %%
 # Imports and Model Definition

docs/v1.4.0/_downloads/e550c5f53cc43e11aa6da8cfb79b54df/dynamo_compile_transformers_example.py

@@ -4,7 +4,8 @@
 Compiling a Transformer using torch.compile and TensorRT
 ==============================================================
 
-This interactive script is intended as a sample of the `torch_tensorrt.dynamo.compile` workflow on a transformer-based model."""
+This interactive script is intended as a sample of the `torch_tensorrt.dynamo.compile` workflow on a transformer-based model.
+"""
 
 # %%
 # Imports and Model Definition

examples/dynamo/torch_compile_advanced_usage.py

@@ -4,7 +4,8 @@
 Torch Compile Advanced Usage
 ======================================================
 
-This interactive script is intended as an overview of the process by which `torch_tensorrt.compile(..., ir="torch_compile", ...)` works, and how it integrates with the `torch.compile` API."""
+This interactive script is intended as an overview of the process by which `torch_tensorrt.compile(..., ir="torch_compile", ...)` works, and how it integrates with the `torch.compile` API.
+"""
 
 # %%
 # Imports and Model Definition

examples/dynamo/torch_compile_resnet_example.py

@@ -4,7 +4,8 @@
 Compiling ResNet with dynamic shapes using the `torch.compile` backend
 ==========================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a ResNet model."""
+This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a ResNet model.
+"""
 
 # %%
 # Imports and Model Definition

examples/dynamo/torch_compile_transformers_example.py

@@ -4,7 +4,8 @@
 Compiling BERT using the `torch.compile` backend
 ==============================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a BERT model."""
+This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a BERT model.
+"""
 
 # %%
 # Imports and Model Definition

examples/dynamo/torch_export_cudagraphs.py

@@ -4,7 +4,8 @@
 Torch Export with Cudagraphs
 ======================================================
 
-This interactive script is intended as an overview of the process by which the Torch-TensorRT Cudagraphs integration can be used in the `ir="dynamo"` path. The functionality works similarly in the `torch.compile` path as well."""
+This interactive script is intended as an overview of the process by which the Torch-TensorRT Cudagraphs integration can be used in the `ir="dynamo"` path. The functionality works similarly in the `torch.compile` path as well.
+"""
 
 # %%
 # Imports and Model Definition

examples/dynamo/torch_export_gpt2.py

@@ -4,7 +4,8 @@
 Compiling GPT2 using the dynamo backend
 ==========================================================
 
-This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model."""
+This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model.
+"""
 
 # %%
 # Imports and Model Definition

examples/dynamo/torch_export_llama2.py

@@ -4,7 +4,8 @@
 Compiling Llama2 using the dynamo backend
 ==========================================================
 
-This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model."""
+This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model.
+"""
 
 # %%
 # Imports and Model Definition

py/torch_tensorrt/_Input.py

@@ -261,7 +261,7 @@ def _supported_input_size_type(input_size: Any) -> bool:
 
     @staticmethod
     def _parse_tensor_domain(
-        domain: Optional[Tuple[float, float]]
+        domain: Optional[Tuple[float, float]],
     ) -> Tuple[float, float]:
         """
         Produce a tuple of integers which specifies a tensor domain in the interval format: [lo, hi)

py/torch_tensorrt/_enums.py

@@ -1200,7 +1200,7 @@ def _from(
 
     @classmethod
     def try_from(
-        c: Union[trt.EngineCapability, EngineCapability]
+        c: Union[trt.EngineCapability, EngineCapability],
     ) -> Optional[EngineCapability]:
         """Create a Torch-TensorRT engine capability enum from a TensorRT engine capability enum.
 

py/torch_tensorrt/dynamo/conversion/_TRTBuilderMonitor.py

@@ -53,13 +53,13 @@ def _redraw(self, *, blank_lines: int = 0) -> None:
         if self._render:
 
             def clear_line() -> None:
-                print("\x1B[2K", end="")
+                print("\x1b[2K", end="")
 
             def move_to_start_of_line() -> None:
-                print("\x1B[0G", end="")
+                print("\x1b[0G", end="")
 
             def move_cursor_up(lines: int) -> None:
-                print("\x1B[{}A".format(lines), end="")
+                print("\x1b[{}A".format(lines), end="")
 
             def progress_bar(steps: int, num_steps: int) -> str:
                 INNER_WIDTH = 10

py/torch_tensorrt/dynamo/conversion/impl/activation/ops.py

@@ -247,7 +247,7 @@ def hard_sigmoid(
     operation_type = trt.ActivationType.HARD_SIGMOID
 
     def hard_sigmoid_dyn_range_fn(
-        dyn_range: Tuple[float, float]
+        dyn_range: Tuple[float, float],
     ) -> Tuple[float, float]:
         def hard_sigmoid_fn(x: float) -> float:
             return max(0, min(1, alpha * x + beta))
@@ -310,7 +310,7 @@ def thresholded_relu(
     operation_type = trt.ActivationType.THRESHOLDED_RELU
 
     def thresholded_relu_dyn_range_fn(
-        dyn_range: Tuple[float, float]
+        dyn_range: Tuple[float, float],
     ) -> Tuple[float, float]:
         def thresholded_relu_fn(x: float) -> float:
             return x if x > alpha else 0

py/torch_tensorrt/dynamo/utils.py

@@ -465,7 +465,7 @@ def to_torch_device(device: Optional[Union[Device, torch.device, str]]) -> torch
 
 
 def to_torch_tensorrt_device(
-    device: Optional[Union[Device, torch.device, str]]
+    device: Optional[Union[Device, torch.device, str]],
 ) -> Device:
     """Cast a device-type to torch_tensorrt.Device
 

py/torch_tensorrt/fx/test/converters/acc_op/test_where.py

@@ -101,7 +101,7 @@ def __init__(self, x_shape, y_shape):
             def forward(self, condition):
                 return torch.where(condition, self.x, self.y)
 
-        inputs = [(torch.randn(condition_shape) > 0)]
+        inputs = [torch.randn(condition_shape) > 0]
         self.run_test(
             Where(x_shape, y_shape),
             inputs,

py/torch_tensorrt/fx/tracer/acc_tracer/acc_tracer.py

@@ -10,7 +10,6 @@
 from typing import (
     Any,
     Callable,
-    cast,
     Dict,
     Iterable,
     Optional,
@@ -19,6 +18,7 @@
     Tuple,
     Type,
     Union,
+    cast,
 )
 
 import torch
@@ -32,7 +32,6 @@
 
 from . import acc_normalizer, acc_ops, acc_shape_prop, acc_utils  # noqa: F401
 
-
 _LOGGER = logging.getLogger(__name__)
 
 
@@ -517,7 +516,7 @@ def _replace_transpose_last_dims_impl(
     changed = False
 
     def _calculate_dim(
-        transpose_dim: Union[torch.fx.Node, int]
+        transpose_dim: Union[torch.fx.Node, int],
     ) -> Union[torch.fx.Node, int]:
         nonlocal transpose_input_node
         nonlocal changed