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Commit 94509fa9 authored by tomrink's avatar tomrink
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......@@ -21,7 +21,7 @@ LOG_DEVICE_PLACEMENT = False
PROC_BATCH_SIZE = 4
PROC_BATCH_BUFFER_SIZE = 5000
NumClasses = 3
NumClasses = 5
if NumClasses == 2:
NumLogits = 1
else:
......@@ -37,7 +37,7 @@ NOISE_TRAINING = False
NOISE_STDDEV = 0.01
DO_AUGMENT = True
DO_SMOOTH = True
DO_SMOOTH = False
SIGMA = 1.0
DO_ZERO_OUT = False
DO_ESPCN = False # Note: If True, cannot do mixed resolution input fields (Adjust accordingly below)
......@@ -275,15 +275,6 @@ class SRCNN:
self.OUT_OF_RANGE = False
# self.abi = None
# self.temp = None
# self.wv = None
# self.lbfp = None
# self.sfc = None
# self.in_mem_data_cache = {}
# self.in_mem_data_cache_test = {}
self.model = None
self.optimizer = None
self.ema = None
......@@ -314,11 +305,6 @@ class SRCNN:
self.test_data_files = None
self.test_label_files = None
# self.train_data_nda = None
# self.train_label_nda = None
# self.test_data_nda = None
# self.test_label_nda = None
# self.n_chans = len(data_params_half) + len(data_params_full) + 1
self.n_chans = 5
......@@ -366,10 +352,6 @@ class SRCNN:
# input_data = np.concatenate(data_s)
# input_label = np.concatenate(label_s)
DO_ADD_NOISE = False
if is_training and NOISE_TRAINING:
DO_ADD_NOISE = True
data_norm = []
for param in data_params_half:
idx = params.index(param)
......@@ -381,8 +363,6 @@ class SRCNN:
tmp = get_grid_cell_mean(tmp)
tmp = tmp[:, 0:66, 0:66]
tmp = normalize(tmp, param, mean_std_dct)
if DO_ADD_NOISE:
tmp = add_noise(tmp, noise_scale=NOISE_STDDEV)
data_norm.append(tmp)
for param in data_params_full:
......@@ -412,13 +392,7 @@ class SRCNN:
tmp = tmp[:, 0:66, 0:66]
if label_param != 'cloud_probability':
tmp = normalize(tmp, label_param, mean_std_dct)
if DO_ADD_NOISE:
tmp = add_noise(tmp, noise_scale=NOISE_STDDEV)
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)
data_norm.append(tmp)
# ---------
data = np.stack(data_norm, axis=3)
......
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