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make changes for pytorch 1.5.1 eia #102

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make changes for pytorch 1.5.1 eia #102

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15 changes: 11 additions & 4 deletions src/sagemaker_pytorch_serving_container/default_pytorch_inference_handler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@
import os
import textwrap

import torch
import torch, torcheia
from sagemaker_inference import (
content_types,
decoder,
Expand All @@ -28,6 +28,9 @@
INFERENCE_ACCELERATOR_PRESENT_ENV = "SAGEMAKER_INFERENCE_ACCELERATOR_PRESENT"
DEFAULT_MODEL_FILENAME = "model.pt"

torch._C._jit_set_profiling_executor(False)
device = torch.device("cpu")


class DefaultPytorchInferenceHandler(default_inference_handler.DefaultInferenceHandler):
VALID_CONTENT_TYPES = (content_types.JSON, content_types.NPY)
Expand All @@ -47,7 +50,11 @@ def default_model_fn(self, model_dir):
raise FileNotFoundError("Failed to load model with default model_fn: missing file {}."
.format(DEFAULT_MODEL_FILENAME))
# Client-framework is CPU only. But model will run in Elastic Inference server with CUDA.
return torch.jit.load(model_path, map_location=torch.device('cpu'))
model = torch.jit.load(model_path, map_location=torch.device('cpu'))
# attach_eia() is introduced in PyTorch Elastic Inference 1.5.1
# by default attach to the 0th device
model = torcheia.jit.attach_eia(model, 0)
return model
else:
raise NotImplementedError(textwrap.dedent("""
Please provide a model_fn implementation.
Expand Down Expand Up @@ -86,8 +93,8 @@ def default_predict_fn(self, data, model):
model = model.to(device)
input_data = data.to(device)
model.eval()
with torch.jit.optimized_execution(True, {"target_device": "eia:0"}):
output = model(input_data)
with torch.jit.optimized_execution(True):
output = model.forward(input_data)
else:
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = model.to(device)
Expand Down