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Fix unit tests for tensorflow 2.3. #16

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Aug 6, 2020
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Fix unit tests for tensorflow 2.3. #16

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12 changes: 6 additions & 6 deletions delta/ml/predict.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,8 +64,8 @@ def _process_block(self, pred_image, x, y, labels):
"""

def _predict_array(self, data):
net_input_shape = self._model.get_input_shape_at(0)[1:]
net_output_shape = self._model.get_output_shape_at(0)[1:]
net_input_shape = self._model.input_shape[1:]
net_output_shape = self._model.output_shape[1:]

assert net_input_shape[2] == data.shape[2],\
'Model expects %d input channels, data has %d channels' % (net_input_shape[2], data.shape[2])
Expand Down Expand Up @@ -101,8 +101,8 @@ def predict(self, image, label=None, input_bounds=None):
Results are limited to `input_bounds`. Returns output, the meaning of which
depends on the subclass.
"""
net_input_shape = self._model.get_input_shape_at(0)[1:]
net_output_shape = self._model.get_output_shape_at(0)[1:]
net_input_shape = self._model.input_shape[1:]
net_output_shape = self._model.output_shape[1:]
offset_r = -net_input_shape[0] + net_output_shape[0]
offset_c = -net_input_shape[1] + net_output_shape[1]
block_size_x = net_input_shape[0] * (_TILE_SIZE // net_input_shape[0])
Expand Down Expand Up @@ -166,7 +166,7 @@ def __init__(self, model, output_image=None, show_progress=False,
self._errors = None

def _initialize(self, shape, label, image):
net_output_shape = self._model.get_output_shape_at(0)[1:]
net_output_shape = self._model.output_shape[1:]
self._num_classes = net_output_shape[-1]
if label:
self._errors = np.zeros(shape, dtype=np.bool)
Expand Down Expand Up @@ -244,7 +244,7 @@ def __init__(self, model, output_image=None, show_progress=False, transform=None
self._transform = transform

def _initialize(self, shape, label, image):
net_output_shape = self._model.get_output_shape_at(0)[1:]
net_output_shape = self._model.output_shape[1:]
if self._output_image is not None:
dtype = np.float32 if self._transform is None else self._transform[1]
bands = net_output_shape[-1] if self._transform is None else self._transform[2]
Expand Down
4 changes: 2 additions & 2 deletions delta/ml/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -180,8 +180,8 @@ def train(model_fn, dataset : ImageryDataset, training_spec):
model.compile(optimizer=training_spec.optimizer, loss=loss,
metrics=training_spec.metrics)

input_shape = model.get_input_at(0).shape
output_shape = model.get_output_at(0).shape
input_shape = model.input_shape
output_shape = model.output_shape
chunk_size = input_shape[1]

assert len(input_shape) == 4, 'Input to network is wrong shape.'
Expand Down