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Commit e96e548c authored by tomrink's avatar tomrink
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......@@ -24,12 +24,12 @@ else:
NumLogits = NumClasses
BATCH_SIZE = 128
NUM_EPOCHS = 80
NUM_EPOCHS = 60
TRACK_MOVING_AVERAGE = False
EARLY_STOP = True
NOISE_TRAINING = True
NOISE_TRAINING = False
NOISE_STDDEV = 0.001
DO_AUGMENT = True
......@@ -270,9 +270,9 @@ class SRCNN:
else:
if DO_ADD_NOISE:
tmp = add_noise(tmp, noise_scale=NOISE_STDDEV)
tmp = np.where(tmp < 0.0, 0.0, tmp)
tmp = np.where(tmp > 1.0, 1.0, tmp)
tmp = np.where(np.isnan(tmp), 0, tmp)
tmp = np.where(tmp < 0.0, 0.0, tmp)
tmp = np.where(tmp > 1.0, 1.0, tmp)
tmp = resample_2d_linear(x_2, y_2, tmp, t, s)
data_norm.append(tmp)
# ---------
......@@ -408,7 +408,7 @@ class SRCNN:
activation = tf.nn.relu
momentum = 0.99
num_filters = 128
num_filters = 32
input_2d = self.inputs[0]
print('input: ', input_2d.shape)
......@@ -740,7 +740,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
grd_c = resample_2d_linear_one(x_2, y_2, grd_c, t, s)
print(grd_a.shape, grd_b.shape, grd_c.shape)
data = np.stack([grd_a, grd_b, grd_c], axis=2)
# data = np.stack([grd_a, grd_b, grd_c], axis=2)
data = np.stack([grd_c], axis=2)
data = np.expand_dims(data, axis=0)
nn = SRCNN()
......
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