def _init_conv_layer_random(self, ilayer):
# determine wih type of layer we want
# first layer is a conv
# we can't have 2 pool in a row
if ilayer == 0:
name = self.conv_types[0]
# if rpevious layer is pool, next can't be pool
elif self.conv_layers[ilayer - 1].__name__ == 'pool':
name = np.random.choice(self.conv_types[:-1])
# else it can be anything
else:
name = np.random.choice(self.conv_types)
# init the parms of the layer
# each layer type has its own params
# the output/input size matching is done automatically
if name == 'conv':
params = {}
params['name'] = name
if ilayer == 0:
params['input_size'] = -1 # fixed by input shape
else:
for isearch in range(ilayer - 1, -1, -1):
if self.conv_layers[isearch].__name__ == 'conv':
params['input_size'] = self.conv_layers[
isearch].output_size
break
params['output_size'] = np.random.choice(
self.conv_params['output_size'])
params['kernel_size'] = np.random.choice(
self.conv_params['kernel_size'])
params['post'] = np.random.choice(self.post_types)
if name == 'pool':
params = {}
params['name'] = name
params['kernel_size'] = np.random.choice(
self.pool_params['kernel_size'])
params['post'] = np.random.choice(self.post_types)
if name == 'dropout':
params = {}
params['name'] = name
params['percent'] = np.random.choice(
self.dropout_params['percent'])
# create the current layer class instance
# and initialize if with the __init_from_dict__() method
current_layer = ast.list_eval(params['name'])()
current_layer.__init_from_dict__(params)
self.conv_layers.append(current_layer)
def _init_fc_layer_random(self, ilayer):
# init the parms of the layer
# each layer type has its own params
# the output/input size matching is done automatically
name = 'fc' # so far only fc layer here
params = {}
params['name'] = name
if ilayer == 0:
params['input_size'] = -1 # fixed by the conv layers
else:
params['input_size'] = self.fc_layers[ilayer - 1].output_size
params['output_size'] = np.random.choice(self.fc_params['output_size'])
params['post'] = np.random.choice(self.post_types)
current_layer = ast.list_eval(params['name'])()
current_layer.__init_from_dict__(params)
self.fc_layers.append(current_layer)
def render_transfer_file(self, restrict_currencies=None):
if restrict_currencies and type(restrict_currencies) == str:
restrict_currencies = ast.list_eval(restrict_currencies)
# collect task information
if self.aggregated == 1:
""" aggregated method """
data = {'transactions': self.get_aggregated_transactions()}
else:
# normal method (each document)
data = {
'transactions':
self.get_individual_transactions(restrict_currencies)
}
content = frappe.render_template(
'erpnextswiss/erpnextswiss/doctype/abacus_export_file/transfer_file.html',
data)
return {'content': content}