empty_memory_format evaluator

[apbose]

Description

Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.

Fixes # (issue)

Type of change

Please delete options that are not relevant and/or add your own.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

Checklist:

• My code follows the style guidelines of this project (You can use the linters)
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas and hacks
• I have made corresponding changes to the documentation
• I have added tests to verify my fix or my feature
• New and existing unit tests pass locally with my changes
• I have added the relevant labels to my PR in so that relevant reviewers are notified

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/ops_evaluators.py	2024-05-24 00:12:59.638980+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/ops_evaluators.py	2024-05-24 00:14:55.849732+00:00
@@ -87,10 +87,11 @@
    kwargs: Dict[str, Argument],
    name: str,
) -> Union[TRTTensor, Sequence[TRTTensor]]:
    return np.random.randn(*args[0])

+
def randperm_validator(randperm_node: Node) -> bool:
    dtype = randperm_node.kwargs.get("dtype", None)
    layout = randperm_node.kwargs.get("layout", None)
    input = randperm_node.args[0]
    if not isinstance(input, int):
@@ -116,10 +117,11 @@
    args: Tuple[Argument, ...],
    kwargs: Dict[str, Argument],
    name: str,
) -> Union[TRTTensor, Sequence[TRTTensor]]:
    return np.random.permutation(args[0])
+

def empty_validator(empty_node: Node) -> bool:
    layout = empty_node.kwargs.get("layout", None)
    pin_memory = empty_node.kwargs.get("pin_memory", None)
    memory_format = empty_node.kwargs.get("memory_format", None)
@@ -162,8 +164,5 @@
    elif memory_format == torch.channels_last_3d:
        # shape of args[0] must be 5
        empty_tensor = empty_tensor.to(memory_format=torch.channels_last_3d)

    return empty_tensor
-
-
-

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/ops_evaluators.py	2024-05-24 00:13:13.183345+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/ops_evaluators.py	2024-05-24 00:15:09.256602+00:00
@@ -87,10 +87,11 @@
    kwargs: Dict[str, Argument],
    name: str,
) -> Union[TRTTensor, Sequence[TRTTensor]]:
    return np.random.randn(*args[0])

+
def randperm_validator(randperm_node: Node) -> bool:
    dtype = randperm_node.kwargs.get("dtype", None)
    layout = randperm_node.kwargs.get("layout", None)
    input = randperm_node.args[0]
    if not isinstance(input, int):
@@ -116,10 +117,11 @@
    args: Tuple[Argument, ...],
    kwargs: Dict[str, Argument],
    name: str,
) -> Union[TRTTensor, Sequence[TRTTensor]]:
    return np.random.permutation(args[0])
+

def empty_validator(empty_node: Node) -> bool:
    layout = empty_node.kwargs.get("layout", None)
    pin_memory = empty_node.kwargs.get("pin_memory", None)
    memory_format = empty_node.kwargs.get("memory_format", None)
@@ -162,8 +164,5 @@
    elif memory_format == torch.channels_last_3d:
        # shape of args[0] must be 5
        empty_tensor = empty_tensor.to(memory_format=torch.channels_last_3d)

    return empty_tensor
-
-
-

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/ops_evaluators.py	2024-05-24 00:13:23.345164+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/ops_evaluators.py	2024-05-24 00:15:15.812085+00:00
@@ -87,10 +87,11 @@
    kwargs: Dict[str, Argument],
    name: str,
) -> Union[TRTTensor, Sequence[TRTTensor]]:
    return np.random.randn(*args[0])

+
def randperm_validator(randperm_node: Node) -> bool:
    dtype = randperm_node.kwargs.get("dtype", None)
    layout = randperm_node.kwargs.get("layout", None)
    input = randperm_node.args[0]
    if not isinstance(input, int):
@@ -116,10 +117,11 @@
    args: Tuple[Argument, ...],
    kwargs: Dict[str, Argument],
    name: str,
) -> Union[TRTTensor, Sequence[TRTTensor]]:
    return np.random.permutation(args[0])
+

def empty_validator(empty_node: Node) -> bool:
    layout = empty_node.kwargs.get("layout", None)
    pin_memory = empty_node.kwargs.get("pin_memory", None)
    memory_format = empty_node.kwargs.get("memory_format", None)
@@ -162,8 +164,5 @@
    elif memory_format == torch.channels_last_3d:
        # shape of args[0] must be 5
        empty_tensor = empty_tensor.to(memory_format=torch.channels_last_3d)

    return empty_tensor
-
-
-

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/ops_evaluators.py	2024-05-24 00:13:45.282455+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/ops_evaluators.py	2024-05-24 00:15:36.375546+00:00
@@ -87,10 +87,11 @@
    kwargs: Dict[str, Argument],
    name: str,
) -> Union[TRTTensor, Sequence[TRTTensor]]:
    return np.random.randn(*args[0])

+
def randperm_validator(randperm_node: Node) -> bool:
    dtype = randperm_node.kwargs.get("dtype", None)
    layout = randperm_node.kwargs.get("layout", None)
    input = randperm_node.args[0]
    if not isinstance(input, int):
@@ -116,10 +117,11 @@
    args: Tuple[Argument, ...],
    kwargs: Dict[str, Argument],
    name: str,
) -> Union[TRTTensor, Sequence[TRTTensor]]:
    return np.random.permutation(args[0])
+

def empty_validator(empty_node: Node) -> bool:
    layout = empty_node.kwargs.get("layout", None)
    pin_memory = empty_node.kwargs.get("pin_memory", None)
    memory_format = empty_node.kwargs.get("memory_format", None)
@@ -162,8 +164,5 @@
    elif memory_format == torch.channels_last_3d:
        # shape of args[0] must be 5
        empty_tensor = empty_tensor.to(memory_format=torch.channels_last_3d)

    return empty_tensor
-
-
-