aclgraph_dump Instructions¶

Overview¶

aclgraph_dump provides the acl_save API that saves tensors as .pt files, which is applicable to the aclgraph scenario.

Preparations¶

Environment Setup

Install msProbe by referring to msProbe Installation Guide.
Include the aclgraph_dump module during compilation and installation from source code.

python3 setup.py bdist_wheel --include-mod=aclgraph_dump --no-check

Install and correctly configure Ascend Extension for PyTorch (torch_npu) and CANN (following msProbe installation requirements).

Constraints

Only the PyTorch framework is supported.
torch_npu is required for compiling aclgraph_dump. If this module is not included, msprobe.lib.aclgraph_dump_ext cannot be imported.

Quick Start¶

The following example shows how to save a tensor in the forward process:

import torch
import torch_npu

from msprobe.pytorch import acl_save

class ToyModel(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.linear = torch.nn.Linear(8, 4)

    def forward(self, x):
        y = self.linear(x)
        # Save the intermediate tensor.
        acl_save(x, "./dump/linear_out.pt")
        return y

if __name__ == "__main__":
    model = ToyMode()
    x = torch.randn(2, 8)
    x.to("npu:4")
    out = model(x)

Data Collection¶

Function Overview¶

acl_save is used to save tensor data. After this API is called, a .pt file is saved.

API Description¶

Prototype

acl_save(x: torch.Tensor, path: str) -> torch.Tensor

Parameters

Parameter	Type	Description	Mandatory (Yes/No)
x	torch.Tensor	Tensor to be saved.	Yes
path	String	Saving path (relative or absolute path), which is of the string type. The name of the actual flushed file is in the format of `{base}_{seq}.pt`. For example, if `./dump/act.pt` is passed, `./dump/act_0.pt` and `./dump/act_1.pt` are actually flushed. (The parent directory `./dump/` must be an existing directory.)	Yes

Returns

Returns a tensor with the same shape as the input, which has no specific meaning and is used only to trigger the saving operation.

Examples¶

1. Single-point saving during inference¶

from msprobe.pytorch import acl_save

logits = model(x)
acl_save(logits, "./dump/logits.pt")

2. Saving the file called for multiple times¶

for step in range(3):
    y = model(x)
    acl_save(y, "./dump/act.pt")

./dump/act_0.pt, ./dump/act_1.pt, and ./dump/act_2.pt are generated.

Output Description¶

Dump Result File¶

After acl_save is called, .pt files are generated in the directory specified by path.

Data Parsing¶

Data is saved in the PyTorch .pt format (pickle serialization) and can be read using torch.load.

import torch

tensor = torch.load("./dump/act_0.pt")

Appendix¶

FAQs¶

Failed to import msprobe.lib.aclgraph_dump_ext

Check:

whether --include-mod=aclgraph_dump has been included during compilation and installation.
whether torch_npu has been installed and the environment variables have been correctly configured.
whether the system is Linux.

Allocate SQ failed

In versions earlier than CANN 8.5 (excluding), Allocate SQ failed may occur because SQ is not reused in earlier versions. You are advised to change CurrentNPUStream to DefaultNPUStream in ccsrc/aclgraph_dump/aclgraph_dump.cpp or upgrade CANN to 8.5.0 or later.