def update_training_info_evaluation_sheet(exp_index,
evaluation_index_list,
debug=True):
add_index_exp = lambda x: x + str(exp_index)
columns_list = list(
map(add_index_exp, get_training_params_colums_in_experiments_sheet()))
training_info_list = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range=columns_list,
debug=debug) #
# paste info to evaluation sheet
for line_index in evaluation_index_list:
add_index_evaluation = lambda x: x + str(line_index)
columns_list = list(
map(add_index_evaluation,
get_training_params_colums_in_evaluation_sheet()))
update_row2sheet(service=get_sheet_service(),
sheet_id=get_evaluation_sheet_id(),
row_starting_position=columns_list[0],
data=training_info_list,
debug=debug) #
def fetch_resize_factor_from_google_sheets(dataset,
subset,
size_set,
model_name,
debug=True):
'''
get model date during training
'''
row_index = get_row_index_from_experiments_sheet(dataset,
subset,
size_set,
model_name,
debug=debug)
factor = get_data_from_sheet(service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range='g' + str(row_index),
debug=debug)[0]
return factor
def fetch_output_stage_from_google_sheets(dataset,
subset,
size_set,
model_name,
debug=True):
'''
get model date during training
'''
row_index = get_row_index_from_experiments_sheet(dataset,
subset,
size_set,
model_name,
debug=debug)
out_stage = get_data_from_sheet(service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range='I' + str(row_index),
debug=debug)[0]
out_stage = out_stage.split('S')
return out_stage[-1]
def fetch_downsample_from_google_sheets(dataset,
subset,
size_set,
model_name,
debug=True):
'''
get downsample factor during training
'''
row_index = get_row_index_from_experiments_sheet(dataset,
subset,
size_set,
model_name,
debug=debug)
downsample = get_data_from_sheet(service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range='H' + str(row_index),
debug=debug)[0]
substrings = downsample.split('x')
return substrings[0]
def update_testing_info_evaluation_sheet(evaluation_index_list,
info_list,
debug=True):
'''
update testing configuration to the record
'''
if debug:
assert len(info_list) == len(
get_testing_params_colums_in_evaluation_sheet()
), 'the information list is not correct %d vs %d' % (len(
info_list), len(get_testing_params_colums_in_evaluation_sheet()))
info_list = list(info_list)
for line_index in evaluation_index_list:
row_starting_position = get_testing_params_colums_in_evaluation_sheet(
)[0] + str(line_index)
update_row2sheet(service=get_sheet_service(),
sheet_id=get_evaluation_sheet_id(),
row_starting_position=row_starting_position,
data=info_list,
debug=debug)
def fetch_fitsize_from_google_sheets(dataset,
subset,
size_set,
model_name,
debug=True):
'''
get input size during training
'''
row_index = get_row_index_from_experiments_sheet(dataset,
subset,
size_set,
model_name,
debug=debug)
inputsize = get_data_from_sheet(service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range='F' + str(row_index),
debug=debug)[0]
substrings = inputsize.split(' ')
width = substrings[0]
height = substrings[2]
return [width, height]
def get_row_index_list_from_evaluation_sheet(
dataset,
subset,
size_set,
evaluation_name,
debug=True): # all evaluated models might not be unique
'''
the returned index is already 1-indexed
'''
if debug:
assert subset in get_compact_subset_list(
) or subset == 'face_old', 'subset is not correct!'
assert size_set in ['resized_4', 'cropped',
'cropped_all'], 'size set is not correct'
column_search_range = range(get_search_range_in_sheet())
# find index in rows in experiments sheet
columns_search_dataset = [
'A%d' % (search_value_tmp + 1)
for search_value_tmp in column_search_range
]
columns_name_dataset = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_evaluation_sheet_id(),
search_range=columns_search_dataset,
debug=debug) #
columns_search_subset = [
'B%d' % (search_value_tmp + 1)
for search_value_tmp in column_search_range
]
columns_name_subset = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_evaluation_sheet_id(),
search_range=columns_search_subset,
debug=debug) #
columns_search_sizeset = [
'C%d' % (search_value_tmp + 1)
for search_value_tmp in column_search_range
]
columns_name_sizeset = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_evaluation_sheet_id(),
search_range=columns_search_sizeset,
debug=debug) #
columns_search_model = [
'D%d' % (search_value_tmp + 1)
for search_value_tmp in column_search_range
]
columns_name_model = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_evaluation_sheet_id(),
search_range=columns_search_model,
debug=debug) #
row_index_list = list()
for row_index in column_search_range:
if columns_name_subset[row_index] == subset and columns_name_sizeset[
row_index] == size_set and columns_name_model[
row_index] == evaluation_name and columns_name_dataset[
row_index] == dataset:
row_index_list.append(row_index + 1)
if len(row_index_list) == 0:
assert False, '%s, %s, %s, %s is not on the search range within the google sheet' % (
dataset, subset, size_set, evaluation_name)
return row_index_list
def get_row_index_from_experiments_sheet(
dataset,
subset,
size_set,
model_name,
debug=True): # all experiments are unique
'''
the returned index is already 1-indexed
'''
if debug:
assert subset in get_compact_subset_list(
) or subset == 'face_old', 'subset is not correct!'
assert size_set in ['resized_4', 'cropped',
'cropped_all'], 'size set is not correct'
column_search_range = range(get_search_range_in_sheet())
# find index in rows in experiments sheet
columns_search_dataset = [
'A%d' % (search_value_tmp + 1)
for search_value_tmp in column_search_range
]
columns_name_dataset = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range=columns_search_dataset,
debug=debug) #
columns_search_subset = [
'B%d' % (search_value_tmp + 1)
for search_value_tmp in column_search_range
]
columns_name_subset = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range=columns_search_subset,
debug=debug) #
columns_search_sizeset = [
'C%d' % (search_value_tmp + 1)
for search_value_tmp in column_search_range
]
columns_name_sizeset = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range=columns_search_sizeset,
debug=debug) #
columns_search_model = [
'D%d' % (search_value_tmp + 1)
for search_value_tmp in column_search_range
]
columns_name_model = get_data_from_sheet(
service=get_sheet_service(),
sheet_id=get_experiments_sheet_id(),
search_range=columns_search_model,
debug=debug) #
row_index_exp = None
for row_index in column_search_range:
if columns_name_subset[row_index] == subset and columns_name_sizeset[
row_index] == size_set and columns_name_model[
row_index] == model_name and columns_name_dataset[
row_index] == dataset:
row_index_exp = row_index + 1
break
if row_index_exp is None:
assert False, 'No entry model (%s, %s, %s, %s) found!' % (
dataset, subset, size_set, model_name)
return row_index_exp