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Autocast numpy objects to appropriate type #384

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Merged
merged 3 commits into from
Aug 27, 2019
Merged

Autocast numpy objects to appropriate type #384

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aa24353
Autocast numpy objects to appropriate type
vishalbollu Aug 27, 2019
9300963
Simplify sklearn handler
vishalbollu Aug 27, 2019
25b9b65
Merge branch 'master' into autocast-numpy
vishalbollu Aug 27, 2019
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2 changes: 1 addition & 1 deletion examples/iris-classifier/handlers/sklearn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@ def pre_inference(sample, metadata):
sample["petal_width"],
]
)
return ((x - scalars["mean"]) / scalars["stddev"]).astype(np.float32)
return (x - scalars["mean"]) / scalars["stddev"]


def post_inference(prediction, metadata):
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14 changes: 11 additions & 3 deletions pkg/workloads/cortex/onnx_serve/api.py
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Expand Up @@ -108,10 +108,18 @@ def transform_to_numpy(input_pyobj, input_metadata):
if dim is None:
target_shape[idx] = 1

if type(input_pyobj) is not np.ndarray:
np_arr = np.array(input_pyobj, dtype=target_dtype)
else:
if type(input_pyobj) is np.ndarray:
np_arr = input_pyobj
if np.issubdtype(np_arr.dtype, np.number) == np.issubdtype(target_dtype, np.number):
if str(np_arr.dtype) != target_dtype:
np_arr = np_arr.astype(target_dtype)
else:
raise ValueError(
"expected dtype '{}' but found '{}'".format(target_dtype, np_arr.dtype)
)
else:
np_arr = np.array(input_pyobj, dtype=target_dtype)

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Can you drop the astype() in the sklearn handler and tolist() in the imagenet handler, and confirm they work?

np_arr = np_arr.reshape(target_shape)
return np_arr
except Exception as e:
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