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4021124 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | # Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import
import argparse
import gzip
import json
import logging
import os
import struct
import mxnet as mx
import numpy as np
def model_fn(model_dir):
import eimx
def read_data_shapes(path, preferred_batch_size=1):
with open(path, "r") as f:
signatures = json.load(f)
data_names = []
data_shapes = []
for s in signatures:
name = s["name"]
data_names.append(name)
shape = s["shape"]
if preferred_batch_size:
shape[0] = preferred_batch_size
data_shapes.append((name, shape))
return data_names, data_shapes
shapes_file = os.path.join(model_dir, "model-shapes.json")
data_names, data_shapes = read_data_shapes(shapes_file)
ctx = mx.cpu()
sym, args, aux = mx.model.load_checkpoint(os.path.join(model_dir, "model"), 0)
sym = sym.optimize_for("EIA")
mod = mx.mod.Module(symbol=sym, context=ctx, data_names=data_names, label_names=None)
mod.bind(for_training=False, data_shapes=data_shapes)
mod.set_params(args, aux, allow_missing=True)
return mod
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