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53 lines
1.4 KiB
53 lines
1.4 KiB
#!/usr/bin/env python3
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# TODO: why are the keras models saved with python 2?
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from __future__ import print_function
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import tensorflow as tf
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import os
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import sys
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import tensorflow.keras as keras
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import numpy as np
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from tensorflow.keras.models import Model
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from tensorflow.keras.models import load_model
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def read(sz):
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dd = []
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gt = 0
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while gt < sz*4:
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st = os.read(0, sz*4 - gt)
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assert(len(st) > 0)
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dd.append(st)
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gt += len(st)
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return np.fromstring(b''.join(dd), dtype=np.float32)
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def write(d):
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os.write(1, d.tobytes())
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def run_loop(m):
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isize = m.inputs[0].shape[1]
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osize = m.outputs[0].shape[1]
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print("ready to run keras model %d -> %d" % (isize, osize), file=sys.stderr)
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while 1:
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idata = read(isize).reshape((1, isize))
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ret = m.predict_on_batch(idata)
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write(ret)
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if __name__ == "__main__":
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print(tf.__version__, file=sys.stderr)
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m = load_model(sys.argv[1])
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print(m, file=sys.stderr)
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bs = [int(np.product(ii.shape[1:])) for ii in m.inputs]
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ri = keras.layers.Input((sum(bs),))
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tii = []
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acc = 0
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for i, ii in enumerate(m.inputs):
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print(ii, file=sys.stderr)
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ti = keras.layers.Lambda(lambda x: x[:,acc:acc+bs[i]], output_shape=(1, bs[i]))(ri)
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acc += bs[i]
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tr = keras.layers.Reshape(ii.shape[1:])(ti)
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tii.append(tr)
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no = keras.layers.Concatenate()(m(tii))
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m = Model(inputs=ri, outputs=[no])
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run_loop(m)
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