本文整理汇总了Python中lasagne.layers.set_all_param_values方法的典型用法代码示例。如果您正苦于以下问题：Python layers.set_all_param_values方法的具体用法？Python layers.set_all_param_values怎么用？Python layers.set_all_param_values使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类lasagne.layers的用法示例。
在下文中一共展示了layers.set_all_param_values方法的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: loadModel
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def loadModel(filename):
print "IMPORTING MODEL PARAMS...",
net_filename = MODEL_PATH + filename
with open(net_filename, 'rb') as f:
data = pickle.load(f)
#for training, we only want to load the model params
net = data['net']
params = l.get_all_param_values(net)
if LOAD_OUTPUT_LAYER:
l.set_all_param_values(NET, params)
else:
l.set_all_param_values(l.get_all_layers(NET)[:-1], params[:-2])
print "DONE!" 示例2: loadPretrained
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def loadPretrained(net):
if cfg.MODEL_NAME:
# Load saved model
n, c = io.loadModel(cfg.MODEL_NAME)
# Set params
params = l.get_all_param_values(n)
if cfg.LOAD_OUTPUT_LAYER:
l.set_all_param_values(net, params)
else:
l.set_all_param_values(l.get_all_layers(net)[:-1], params[:-2])
return net
#################### LOSS FUNCTION ###################### 示例3: split_validation
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def split_validation(classn):
X, inds, coor = load_data();
network, new_params, input_var, aug_var, target_var = build_network_from_ae(classn);
train_fn, new_params_train_fn, val_fn = make_training_functions(network, new_params, input_var, aug_var, target_var);
layers.set_all_param_values(network, pickle.load(open(CNNModel, 'rb')));
A = get_aug_feas(X);
Y = np.zeros((X.shape[0], classn), dtype=np.int32);
# Testing
_, _, _, _, Or, _ = val_fn_epoch(classn, val_fn, X, A, Y);
Or_all = np.zeros(shape=(coor.shape[0],), dtype=np.float32);
Or_all[inds] = Or[:, 0];
fid = open(TileFolder + '/' + heat_map_out, 'w');
for idx in range(0, Or_all.shape[0]):
fid.write('{} {} {}\n'.format(coor[idx][0], coor[idx][1], Or_all[idx]));
fid.close();
return; 示例4: split_validation
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def split_validation(classn):
X, coor = load_data();
network, input_var, target_var = build_network_from_ae(classn);
val_fn = make_training_functions(network, input_var, target_var);
layers.set_all_param_values(network, pickle.load(open(CNNModel, 'rb')));
Y = np.zeros((X.shape[0], classn), dtype=np.int32);
# Testing
_, _, _, Pr, Or, Tr = val_fn_epoch(classn, val_fn, X, Y);
fid = open(TileFolder + '/' + heat_map_out, 'w');
for idx in range(0, Or.shape[0]):
fid.write('{} {} {}\n'.format(coor[idx][0], coor[idx][1], Or[idx][0]));
fid.close();
return Pr, Or, Tr; 开发者ID:SBU-BMI，项目名称:u24_lymphocyte，代码行数:20，代码来源:deep_conv_classification_alt51_luad10_luad10in20_brca10x1_heatmap.py
示例5: split_validation
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def split_validation(classn, valid_num):
X_train, y_train, X_test, y_test = load_data(classn, valid_num);
network, new_params, input_var, aug_var, target_var = build_network_from_ae(classn);
layers.set_all_param_values(network, pickle.load(open('model_vals/deep_conv_classification_lpatch_alt1.py_e10_cv0.pkl', 'rb')));
train_fn, new_params_train_fn, val_fn = make_training_functions(network, new_params, input_var, aug_var, target_var);
a_train = get_aug_feas(X_train);
a_test = get_aug_feas(X_test);
#train_round(31, network, valid_num, new_params_train_fn, val_fn, classn, X_train, a_train, y_train, X_test, a_test, y_test);
LearningRate.set_value(np.float32(0.03*LearningRate.get_value()));
train_round(240, network, valid_num, train_fn, val_fn, classn, X_train, a_train, y_train, X_test, a_test, y_test);
# Testing
_, _, _, Pr, Or, Tr = val_fn_epoch(classn, val_fn, X_test, a_test, y_test);
return Pr, Or, Tr; 示例6: split_validation
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def split_validation(classn):
X, coor = load_data();
network, new_params, input_var, aug_var, target_var = build_network_from_ae(classn);
train_fn, new_params_train_fn, val_fn = make_training_functions(network, new_params, input_var, aug_var, target_var);
layers.set_all_param_values(network, pickle.load(open(CNNModel, 'rb')));
A = get_aug_feas(X);
Y = np.zeros((X.shape[0], classn), dtype=np.int32);
# Testing
_, _, _, Pr, Or, Tr = val_fn_epoch(classn, val_fn, X, A, Y);
fid = open(TileFolder + '/' + heat_map_out, 'w');
for idx in range(0, Or.shape[0]):
fid.write('{} {} {}\n'.format(coor[idx][0], coor[idx][1], Or[idx][0]));
fid.close();
return Pr, Or, Tr; 开发者ID:SBU-BMI，项目名称:u24_lymphocyte，代码行数:21，代码来源:deep_conv_classification_alt48_luad10_luad10in20_brca10x1_heatmap.py
示例7: split_validation
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def split_validation(classn, valid_num):
X_train, y_train, X_test, y_test = load_data(classn, valid_num);
network, new_params, input_var, aug_var, target_var = build_network_from_ae(classn);
layers.set_all_param_values(network, pickle.load(open('model_vals/deep_conv_classification_lpatch_alt2.py_e15_cv0.pkl', 'rb')));
train_fn, new_params_train_fn, val_fn = make_training_functions(network, new_params, input_var, aug_var, target_var);
a_train = get_aug_feas(X_train);
a_test = get_aug_feas(X_test);
#train_round(16, network, valid_num, new_params_train_fn, val_fn, classn, X_train, a_train, y_train, X_test, a_test, y_test);
LearningRate.set_value(np.float32(0.10*LearningRate.get_value()));
train_round(240, network, valid_num, train_fn, val_fn, classn, X_train, a_train, y_train, X_test, a_test, y_test);
# Testing
_, _, _, Pr, Or, Tr = val_fn_epoch(classn, val_fn, X_test, a_test, y_test);
return Pr, Or, Tr; 示例8: split_validation
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def split_validation(classn, valid_num):
X_train, y_train, X_test, y_test = load_data(classn, valid_num);
network, new_params, input_var, aug_var, target_var = build_network_from_ae(classn);
layers.set_all_param_values(network, pickle.load(open('model_vals/deep_conv_classification_lpatch_alt1.py_e30_cv0.pkl', 'rb')));
train_fn, new_params_train_fn, val_fn = make_training_functions(network, new_params, input_var, aug_var, target_var);
a_train = get_aug_feas(X_train);
a_test = get_aug_feas(X_test);
#train_round(31, network, valid_num, new_params_train_fn, val_fn, classn, X_train, a_train, y_train, X_test, a_test, y_test);
LearningRate.set_value(np.float32(0.03*LearningRate.get_value()));
train_round(240, network, valid_num, train_fn, val_fn, classn, X_train, a_train, y_train, X_test, a_test, y_test);
# Testing
_, _, _, Pr, Or, Tr = val_fn_epoch(classn, val_fn, X_test, a_test, y_test);
return Pr, Or, Tr; 示例9: split_validation
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def split_validation(classn):
network, new_params, input_var, aug_var, target_var = build_network_from_ae(classn);
train_fn, new_params_train_fn, val_fn = make_training_functions(network, new_params, input_var, aug_var, target_var);
layers.set_all_param_values(network, pickle.load(open(CNNModel, 'rb')));
# Testing
Or, inds, coor = val_fn_epoch_on_disk(classn, val_fn);
Or_all = np.zeros(shape=(coor.shape[0],), dtype=np.float32);
Or_all[inds] = Or[:, 0];
fid = open(TileFolder + '/' + heat_map_out, 'w');
for idx in range(0, Or_all.shape[0]):
fid.write('{} {} {}\n'.format(coor[idx][0], coor[idx][1], Or_all[idx]));
fid.close();
return; 示例10: loadParams
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def loadParams(net, params):
log.i("IMPORTING MODEL PARAMS...", new_line=False)
if cfg.LOAD_OUTPUT_LAYER:
l.set_all_param_values(net, params)
else:
l.set_all_param_values(l.get_all_layers(net)[:-2], params[:-2])
log.i("DONE!")
return net 示例11: loadParams
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def loadParams(net, params):
log.p('IMPORTING MODEL PARAMS...', new_line=False)
l.set_all_param_values(net, params)
log.p('DONE!')
return net 示例12: load_model
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def load_model(self, load_path):
with open(load_path, 'r') as f:
data = pkl.load(f)
L.set_all_param_values(self.network, data)
for item in self.trackers:
data = pkl.load(f)
L.set_all_param_values(item, data) 示例13: load_model
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def load_model(self, load_path):
with open(load_path, 'r') as f:
data = pkl.load(f)
L.set_all_param_values(self.network, data) 示例14: split_validation
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def split_validation(classn, valid_num):
X_train, y_train, X_test, y_test = load_data(classn, valid_num);
network, new_params, input_var, aug_var, target_var = build_network_from_ae(classn);
train_fn, new_params_train_fn, val_fn = make_training_functions(network, new_params, input_var, aug_var, target_var);
a_train = get_aug_feas(X_train);
a_test = get_aug_feas(X_test);
layers.set_all_param_values(network, pickle.load(open(model_dump + '_e{}_cv{}.pkl'.format(read_epoch, valid_num), 'rb')));
# Testing
_, _, _, Pr, Or, Tr = val_fn_epoch(classn, val_fn, X_test, a_test, y_test);
save_visual_cases(X_test, Or, Tr);
return Pr, Or, Tr; 开发者ID:SBU-BMI，项目名称:u24_lymphocyte，代码行数:16，代码来源:deep_conv_classification_alt48_luad10_skcm10_lr0_deploy.py
示例15: load_model
# 需要导入模块: from lasagne import layers [as 别名]
# 或者: from lasagne.layers import set_all_param_values [as 别名]
def load_model(self, load_path):
with open(load_path, 'r') as f:
data = pickle.load(f)
L.set_all_param_values(self.network, data)