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Commit 290cc719 authored by tomrink's avatar tomrink
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minor

parent 999d6ff7
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...@@ -22,7 +22,7 @@ BATCH_SIZE = 256 ...@@ -22,7 +22,7 @@ BATCH_SIZE = 256
NUM_EPOCHS = 100 NUM_EPOCHS = 100
TRACK_MOVING_AVERAGE = False TRACK_MOVING_AVERAGE = False
EARLY_STOP = True EARLY_STOP = False
TRIPLET = False TRIPLET = False
CONV3D = False CONV3D = False
...@@ -31,6 +31,7 @@ NOISE_TRAINING = False ...@@ -31,6 +31,7 @@ NOISE_TRAINING = False
img_width = 16 img_width = 16
# mean_std_file = homedir+'data/icing/mean_std_no_ice.pkl'
mean_std_file = homedir+'data/icing/mean_std_l1b_no_ice.pkl' mean_std_file = homedir+'data/icing/mean_std_l1b_no_ice.pkl'
f = open(mean_std_file, 'rb') f = open(mean_std_file, 'rb')
mean_std_dct = pickle.load(f) mean_std_dct = pickle.load(f)
...@@ -40,10 +41,10 @@ f.close() ...@@ -40,10 +41,10 @@ f.close()
# 'cld_reff_dcomp', 'cld_opd_dcomp', 'cld_cwp_dcomp', 'iwc_dcomp', 'lwc_dcomp'] # 'cld_reff_dcomp', 'cld_opd_dcomp', 'cld_cwp_dcomp', 'iwc_dcomp', 'lwc_dcomp']
# #'cloud_phase'] # #'cloud_phase']
train_params = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13_3um_nom', 'temp_3_75um_nom', train_params = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13_3um_nom', 'temp_3_75um_nom',
'temp_6_2um_nom', 'temp_6_7um_nom', 'temp_7_3um_nom', 'temp_8_5um_nom', 'temp_9_7um_nom', 'temp_6_2um_nom', 'temp_6_7um_nom', 'temp_7_3um_nom', 'temp_8_5um_nom', 'temp_9_7um_nom',
'refl_0_47um_nom', 'refl_0_65um_nom', 'refl_0_86um_nom', 'refl_1_38um_nom', 'refl_1_60um_nom'] 'refl_0_47um_nom', 'refl_0_65um_nom', 'refl_0_86um_nom', 'refl_1_38um_nom', 'refl_1_60um_nom']
# train_params = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13_3um_nom', 'temp_3_75um_nom', # train_params = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13_3um_nom', 'temp_3_75um_nom',
# 'temp_6_2um_nom', 'temp_6_7um_nom', 'temp_7_3um_nom', 'temp_8_5um_nom', 'temp_9_7um_nom'] # 'temp_6_2um_nom', 'temp_6_7um_nom', 'temp_7_3um_nom', 'temp_8_5um_nom', 'temp_9_7um_nom']
def build_residual_block(input, drop_rate, num_neurons, activation, block_name, doDropout=True, doBatchNorm=True): def build_residual_block(input, drop_rate, num_neurons, activation, block_name, doDropout=True, doBatchNorm=True):
......
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