Python Assignments Dataset c = 0 exit_code = 0 numStDev = 10.0 numStDev = 5 delta = 0.00005 numStDev = 9 even = True even = False partsScanned = 0 numPartsToTry = 1 taken = 0 batchSize = 100 how = "inner" method = "pearson" support = 0.01 use_arrow = True use_arrow = False best_class = 0 max_margin = 0.0 direction = 1 result = 0.0 k1 = 0 k2 = 0 all_equal = True minimum_pandas_version = "0.19.2" have_pandas = True have_pandas = False minimum_pyarrow_version = "0.12.1" have_arrow = True have_arrow = False inner_array_length = 0 start = 0 has_rec_fix = False curr_type = 'datetime64[us]' has_rec_fix = True copied = False copied = True col_by_name = True has_pandas = True has_pandas = False should_write_start_length = True should_write_start_length = False should_process = True should_special_case = False modname = '__main__' unique_id = 0 prev_is_whitespace = True is_impossible = False prev_is_whitespace = False orig_answer_text = "" unique_id = 1000000000 start_offset = 0 out_of_span = False start_position = 0 end_position = 0 out_of_span = True score_null = 1000000 min_null_feature_index = 0 null_start_logit = 0 null_end_logit = 0 final_text = "" total_sum = 0.0 start_prefix = '' start_prefix = 'bert.' index = 0 is_bad = False is_bad = True label = 0 label = 1 t1 = "" t2 = "" masked_token = "[MASK]" current_length = 0 i = 0 a_end = 1 is_random_next = True is_random_next = False offset = 0 start_prefix = 'transformer.' stride = 1 index_summary = '' msg = "Names must be a string when a single level is provided." msg = "'value' must be a scalar, passed: {0}" start_slice = 0 match_axis_length = False mask = False method = 'values' j = 0 bc = 0 _local_template = "Compute %(f)s of group values" dropna = 'all' inference = 'datetime64[ns]' msg = "na_option must be one of 'keep', 'top', or 'bottom'" msg = "Path prefix to option '{option}' is already an option" msg = "Option '{key}' has already been registered" msg = "Option '{key}' is a reserved key" msg = "Option '{key}' has already been defined as deprecated." freq = 'D' msg = 'freq must be specified for bdate_range; use date_range instead' copy = False index = 'minor_axis' columns = 'items' index = 'major_axis' columns = 'minor_axis' how = 'outer' acc = 1 stride = 0 alpha = 0.0 beta = 1.0 dtypes = 'infer' dtype = 'infer' find_dtype = False find_dtype = True dtype = False na_rep = 'NaT' new_style = False tail_pad = 0 result = False align_copy = True align_copy = False dtype = 'object' require_iso8601 = False format_found = False format_found = True fmt = "{{{body}}}" fmt = "{{{things}}}" pfmt = "{key}: {val}" sep = ',' close = ', ' summary = "" z95 = 1.959963984540054 z99 = 2.5758293035489004 count = 0 tmpl = "{count}{dtype}" size_qualifier = '' tmpl = "{count} non-null {dtype}" count = "" deep = True deep = False size_qualifier = '+' copy = True msg = "expr must be a string to be evaluated, {0} given" msg = 'object of type {typ!r} has no info axis' thresh = 1000 min_periods = 1 c = 1. step = 1 ixify = True ixify = False need_reindex = False need_reindex = True dtype = 'bool' dtype = 'int64' dtype = 'datetime64[ns]' dtype = 'timedelta64[ns]' msg = "invalid ndarray passed to infer_dtype_from_scalar" sort = True _is_table_name = False _SQLALCHEMY_INSTALLED = False msg = "codes need to be array-like integers" msg = "removals must all be in old categories: {not_included!s}" msg = 'invalid na_position: {na_position!r}' allow_fill = True levstring = "" start = True max_width = 0 start = False periods = 0 nb_offset = 1 num_qtrs = 0 num = 0 has_names = False has_names = True match = False msg = "Cannot specify both 'axis' and any of 'index' or 'columns'." msg = "Cannot specify all of '{}', 'index', 'columns'." method = ".apply(<func>)" how = 'E' is_tuple = False is_tuple = True title = 'this page' ncol = 1 coltext = '' nrow = 1 passed_names = True na_count = 0 start = 2 implicit_first_cols = 0 linespec = "" has_none_blocks = False msg = "invalid dtype determination in get_concat_dtype" has_none_blocks = True upcast_cls = 'category' upcast_cls = 'datetimetz' upcast_cls = 'bool' upcast_cls = 'object' upcast_cls = 'datetime' upcast_cls = 'timedelta' upcast_cls = 'float' has_bad_values = False has_bad_values = True NS_PER_DAY = 24 * 3600 * 1000 * 1000 * 1000 ws = '' max_str_len = 244 max_str_len = 2045 null_string = '\x00' duplicate_var_id = 0 _WARN = False future = "a TypeError will be raised" left_closed = False right_closed = False left_closed = True right_closed = True freq_infer = False freq_infer = True na_msg = 'cannot index with vector containing NA / NaN values' excel = True typ = 'category' typ = 'sparse' typ = 'range' typ = 'datetime' typ = 'timedelta' typ = 'object' typ = 'bool' ordered = False ROW_HEADING_CLASS = "row_heading" COL_HEADING_CLASS = "col_heading" INDEX_NAME_CLASS = "index_name" DATA_CLASS = "data" BLANK_CLASS = "blank" BLANK_VALUE = "" other = '' msg = "`text_color_threshold` must be a value from 0 to 1." css = 'width: 10em; height: 80%;' auto_close = False auto_close = True exists = False nan_rep = 'nan' index = False tt = 'legacy_panel' pt = 'frame_table' tt = 'generic_table' tt = 'legacy_frame' tt = 'appendable_series' tt = 'appendable_panel' tt = 'appendable_multiseries' tt = 'appendable_frame' tt = 'appendable_ndim' tt = 'appendable_multiframe' chunksize = 100000 multi_message = '' date_format = 'iso' date_format = 'epoch' tupleize_cols = False n = 1 axis = 0 ax = 1 msg = "rank does not make sense when ndim > 2" numeric_only = True msg = "Boolean array expected for the condition, not {dtype}" try_quick = True align = True try_quick = False msg = 'Freq was not given and was not set in the index' msg = "describe is not implemented on Panel objects." msg = "exclude must be None when include is 'all'" skipna = True is_nested_renamer = False is_nested_renamer = True dtype = "object" _PATHLIB_INSTALLED = True _PY_PATH_INSTALLED = True _PATHLIB_INSTALLED = False _PY_PATH_INSTALLED = False msg = "Invalid file path or buffer object type: {_type}" compression = 'gzip' copy_made = False copy_made = True format = "xport" format = "sas7bdat" is_series = False is_index = False is_scalars = False is_series = True is_index = True is_scalars = True msg = "fillna with 'method' requires high memory usage." engine = 'numexpr' engine = 'python' first_expr = True target_modified = False target_modified = True first_expr = False error_msg = "Input must be a list / sequence of array-likes." msg = 'Cannot infer number of levels from empty list' objsize = 24 changed = False changed = True level = 0 dtype = 'category' ndtype = 'string' ndtype = 'object' flip_order = False flip_order = True is_timedelta = False is_timedelta = True int_as_wall_time = False nonexistent = 'NaT' nonexistent = 'raise' current_module = 'pandas' position = 'autosummary' position = 'items' examples_errs = '' fmt = '0' ascending = True convert = True ndim = 1 mode = 'a+b' mode = 'wb' typ = 'interval_index' typ = 'interval_array' dtype = True convert_axes = True needs_new_obj = False needs_new_obj = True one_day_nanos = (86400 * 1e9) format = 'sub_day' format = 'long' last_index = 0 is_dot_col = False my_str = '...' my_str = '..' dot_mode = 'left' cwidth = 4 dot_mode = 'right' counter = 0 encoding = 'utf-8' too_long = False close = False close = True need_save = False need_save = True int_use_threads = 1 msg = '{name!r} is too specific of a frequency, try passing {type!r}' msg_sorted = "{side} keys must be sorted" msg_missings = "Merge keys contain null values on {side} side" case = True msg = 'expected a string object, not {0}' method = 'find' method = 'rfind' msg = 'fillchar must be a character, not {0}' msg = 'width must be of integer type, not {0}' repl = '' y = '' join_warn = False depr_warn = False depr_warn = True sep = '' msg = "Input must be a list-like of list-likes" cmd = "nvidia-smi" have_nvidia_smi = False nvidia_gpu_cnt = 0 have_nvidia_smi = True cmd = "nvidia-smi --query-gpu=memory.total --format=csv,nounits,noheader" max_cuda = "8.0" cur_size = 4 final_message = "You can deactivate this warning by passing `no_check=True`." message = "It's not possible to collate samples of your dataset together in a batch." dirname = 'imagenet' actualclasses = '' nbytes = 0 show_progress = False inputs_seen = 0 changed_cnt = 0 sz = 64 total_params = 0 total_trainable_params = 0 resume=False title = 'Ground truth/Predictions' title = 'Input / Prediction / Target' exception=False unk_id = 3 avg_mom=0.98 phase = 0 stop=False use_relative_links = False use_relative_links = True parsed = "" tabmat = '' ext = '.html' cell_num = 0 last = 0 msg = " at %s (%s)" namespace = "" attributeValue = '' start_cmd = "" start_cmd = "/Applications/Firefox.app/Contents/MacOS/firefox-bin" system = "mac" matched = False matched = True connectable = True result = True cmd = "python -m spacy download {}" n_inputs = 25000 err_path = "" test_text = "Do you like horses?" delimit_docs = "-DOCSTART- -X- O O" test_text = "I like blue eggs" flag = False flag = True dl_tpl = "{m}-{v}/{m}-{v}.tar.gz#egg={m}=={v}" print_header = True print_header = False rbracket = 0 template = "M{x},{y} C{x},{c} {e},{c} {e},{y}" template = "M{x},{y} {x},{c} {e},{c} {e},{y}" markup = "" iter_since_best = 0 best_score = 0.0 words_seen = 0 checked_for_ner = False has_ner_tags = False checked_for_ner = True suffix = "LOC" suffix = "ORG" suffix = "MISC" title = "Info about spaCy" nr_seen = 0 restore = True restore = False should_yeild = False should_yeild = True summaries_dir = './summaries' c_channels = 1 c_channels = 3 INITIAL_POS = 33 total_expected = 0 value_next = 0.0 memory_size = 0 is_integral = True is_integral = False is_timeseries = True is_loaded = False query = '' is_loaded = True slice_id = 0 datatype = 'UNKNOWN' message = 'Error loading strategy!' metric_type = 'longSum' query_str = '' granularity = 'all' phase = 1 tbl_name = 'wb_health_population' dash_name = "World's Bank Data" slug = 'world_health' exec_sql = '' str_res = '' is_new_obj = True is_new_obj = False limit = 1000 count = 1 limit = 0 order_by_clause = '' where_clause = '' last_log_line = 0 needs_commit = False needs_commit = True attempt = 0 msg = '' separator = ' : ' tbl_name = 'energy_usage' tbl_name = 'flights' valid_cluster = True valid_cluster = False result = "" max_len = 0 max_start_i = 0 all_negative_flag = True all_negative_flag = False row_len = 0 is_first_word = True row = "" is_first_word = False iteration = 0 swapped = True swapped = False k = 0 pos = 0 middle = 0 step = 0 fib_1 = 0 fib_2 = 1 sum = 0 length = 1 count = 9 start = 1 j = 5 max_length = 0 sub_string = '' result = 1 block_prev = 0 result = 2 padding = 0 ten = 0 summ = 0 low = 0 b = 1 different = 0 cost = 0 lt = 0 res = '' max_so_far = 0 current_comp = 0 ab = 0 comb = "00 11 88 69 96" is_negative = False is_negative = True multiplier = 1 res = 0 cur_num = 0 cur_string = '' current = "" mxlen = 256 nboost = 0 num_parallel_tree = 1 context = 'train' context = 'cv' maximize_score = True lib_success = False lib_success = True msg = 'feature_names must have the same length as data' msg = 'Unable to set feature types before setting names' msg = 'feature_types must have the same length as data' need_close = True need_close = False average_over_splits = True importance_type = 'gain' average_over_splits = False importance_type = 'cover' msg = 'feature_names mismatch: {0} {1}' e = 2.0 fs = '' timestamp = 0.0 format = "[%(asctime)s] %(levelname)s:%(name)s:%(message)s" total_cer = 0.0 total_char_length = 0.0 total_wer = 0.0 total_word_length = 0.0 output_filename = 'output_graph.pb' triggered = False triggered = True freq = 1 encoder_archi = "a/a/a/a/a" decoder_archi = "a-sepm/a-sepm/a-moe/a-sepm/a-sepm" pad = "_" nbr_case = 0 suffix = "train" suffix = "dev" suffix = "test" num_threads = 64 prefix = "transformer/body/" postfix_self_attention = "/multihead_attention/dot_product_attention" postfix_encdec = "/multihead_attention/dot_product_attention" total_reward = 0.0 log_all = True err_msg = "T2T: skipped importing {num_missing} data_generators modules." label_key = "labels" label_key = "fine_labels" label_key = "coarse_labels" simulated_rollout_length = 10 base = 100000 precision = 1 recall = 1 num_nonempty_targets = 0 score = 0. stats_wiki_found_refs = 0 num_refs = 0 num_refs_in_wet = 0 start_tag = u"<title>" end_tag = u"</title>" ret = u"" current_pos = 0 ret = 0 num_shards = 1 batch_size_means_tokens = True batch_size_means_tokens = False start_idx = 0 logdet_factor = 1 output = 0.0 objective = 0.0 ret = 0.0 decayed_value = 0.0 ffmpeg = "ffmpeg" n_filters = 64 num_target_frames = 1 msg = 'Unknown padding type: {}.' msg = 'Wrong number of explicit pads for conv: expected {}, got {}.' done = True const_label = 0 ret = 1.0 steps_without_improvement = 0 neg_q_entropy = 0. x_means = 0 extra_loss = 0 mask = True eps = 1e-12 rank_dir = "all" txt = "" stopiters_seen = 0 hp_prefix = "--hp_" in_skip = True lines_read = 0 receptive_field_size = 1. title = "no title" postprocess = False found_sentence = False num_alpha = 0 found_sentence = True err_str = "All environments should have the same action space, but don't." raw_reward = 0.0 processed_reward = 0 multiplier = 2 masking = 1.0 done = False ts = 0 padding_value = 0.0 padding_value = 0 entropy_bonus = 0.0 mnli_filename = "MNLI.zip" _DO_SUMMARIES = False alpha = 0.5 padding = "VALID" is_3d = True is_3d = False num_splits = 16 num_splits = 4 df1 = 0 df2 = 0 dscale = 0 dbias = 0 prefix_size = 1 x_name = "(eager Tensor)" epsilon = 1e-5 mean_rewards = 0 num_dones = 0 step_index = 0 cnn_filename = "cnn_stories.tgz" dailymail_filename = "dailymail_stories.tgz" reading_highlights = False reading_highlights = True filename = "cnndm.train" filename = "cnndm.dev" filename = "cnndm.test" mode_name = "test" mode_name = "train" last_step = 0 prefix_found = False prefix_found = True beam_size = 1 loss = 0.0 decode_length = 1 num_async_replicas = 1 pixel_embedding_size = 64 num_channels = 3 var_epsilon = 1e-09 channels = 3 scope_name = "shared" scope_name = "softmax" reuse = False bias = 0 tag = "train" tag = "eval" tag = "other" chunk_size = 16 * 1024 added = False added = True non_reserved_start_index = 0 min_count = 1 rows = 1 num_saved_frames = 0 split_index = 0 split_begin_index = 0 num_saved_frames_current_rollout = 0 extra_loss = 0.0 epsilon = 1e-3 extra_loss_multiplier = 1e-3 is_padded = False is_padded = True value_rel_embeddings_concat_axis = 0 value_rel_embeddings_concat_axis = 1 total_loss = 0.0 y = 0 dn = 0 a = 4 b = 4 first_depth = 64 init_stddev = 1e-2 lstm_init_stddev = 1e-4 pred_depth = 20 reuse = True kl_loss = 0.0 temperature = 0.0 max_area_width = 1 max_area_height = 1 memory_height = 1 target_tokens_per_batch = 4096 target_images_per_batch = 4 target_images_per_batch = 2 is_4d = False is_4d = True depth = 256 leftovers = "" ret = "" depth = 0 thrown_out_count = 0 diff_char_count = 0 equal_char_count = 0 num_errors = 0 max_match_length = 0 num_distort_cases = 4 ffn_layer = "dense_relu_dense" task_id_start = 0 typename = 'bool' typename = 'int64' typename = 'bytes' typename = 'float' dataset_name = "random" variable_target_shapes = False variable_target_shapes = True last_epoch = 0 axis = 1 axis = 3 loss_num = 0. loss_den = 0. world_model_steps_num = 0 batch_size = 10 output_length = 2048 inputs_per_output = 128 chunk_size = 4 scale = 1.0 total_size = 0 tag = "Trainable Variables" tag = "training_variables/" tag = "tensors/" dir_name = "wikitext-103-raw" dir_name = "wikitext-103" epsilon = 1e-10 worker_per_game = 5 num_eval_samples = 0 beam_score_str = "" total_time_per_step = 0 total_cnt = 0 batch_length = 0 input_type = "text" const_array_size = 10000 input_is_image = False loss = 0 total_sequences = 0 total_input_tokens = 0 total_target_tokens = 0 nonpadding_input_tokens = 0 nonpadding_target_tokens = 0 max_input_length = 0 max_target_length = 0 chars_total = 0 chars_this_file = 0 name = "sgd" name = "rms_prop" original_metric = "l2" original_metric = "ndcg" eval_metric = "multi_logloss" eval_metric = 'binary_logloss' eval_metric = "multi_error" eval_metric = 'binary_error' is_inparameter = False is_inparameter = True has_eqsgn = False has_eqsgn = True idx = 1 idx = 2 options_str = '' aliases_str = '' checks_str = '' data_idx = 0 importance_type_int = 0 importance_type_int = 1 msg = "Training until validation scores don't improve for {} rounds." is_valid_contain_train = False train_data_name = "training" is_valid_contain_train = True nrounds = 5 msg = """more than one metric available, picking one to plot.""" model = "supervised" input = "" file_friendly_logging = True num_neighbors = 0 entity_type = 1 entity_type = 2 entity_type = 3 entity_type = 0 num_entities_in_instance = 0 logical_form = 'Error producing logical form' added_number_filters = False added_number_filters = True need_to_expand = False need_to_expand = True mismatch = True mismatch = False num_brackets = 0 char_index = 0 correct = 0 total_norm = 0 fail = False fail = True span_start = 0 span_end = 0 step_num = 0 best = 1e9 avg_value = 0. num_tries = 0 num_chosen = 0 buffer_index = 0 verb_flag = False verb_flag = True prefix = 'I' prev_label = "O" cur_label = "V" add_to_prediction = True add_to_prediction = False timesteps = 32 batch_size = 32 error = False start_index = 0 error = True answer_index = 1 num_cannot = 0 num_spans = 0 step_num = 1 max_f1 = 0.0 match_flag = False max_em_score = 0.0 max_f1_score = 0.0 max_type = "number" new_label = "*" dims_so_far = 0 dual_message_template = "%s | %8.3f | %8.3f" no_val_message_template = "%s | %8.3f | %8s" no_train_message_template = "%s | %8s | %8.3f" header_template = "%s | %-10s" cycle_weight = 0.0 found = False found = True num_tokens_found = 0 epoch = 0 from_entity = "" to_entity = "" score = 0.0 last_transition_score = 0.0 parsed = 0 total_non_aliases = 0 total_as_count = 0 total_queries_with_weird_as = 0 total = 0 size = 1. attempt_number = 1 magnitude = 1 is_range = False is_range = True num_zeros = 1 pos = 'XX' line_num = 0 parse = "-" lemma = "-" is_aggregated = True is_aggregated = False validation_errors = "" base_location_cost = 0 cost_of_living = 0 card_title = "Welcome" should_end_session = False data_hash = "" allow_credentials = False ALLOW_ORIGIN = "Access-Control-Allow-Origin" ALLOW_HEADERS = "Access-Control-Allow-Headers" ALLOW_METHODS = "Access-Control-Allow-Methods" MAX_AGE = "Access-Control-Max-Age" ALLOW_CREDENTIALS = "Access-Control-Allow-Credentials" principalId = 'user|a1b2c3d4' available_probability = 0.3 start_hour = 10 start_time = '10:00' prefix = 'We have availabilities at ' prefix = 'We have plenty of availability, including ' message_content = 'The time you requested is not available. ' max_conditions = 10 INVALID_ERROR = "Invalid value for 'Cors' property" resource = '${__ApiId__}/authorizers/*' total_wait_time = 0 have_tried = 0 permitted_stage = "*" stage_suffix = "AllStages" stage_suffix = "Stage" fn_num = 0 new_block = '' col_len = 0 ymax = 0 xfer_count = 0 xfer_bytes = 0 width = 25 dummy_axis = 2 word = "" tmp_str = '' tmp_char = '' datasetType = 'instances' datasetType = 'captions' single_rowid = False single_rowid = True anybody_ever_needs_label = False anybody_ever_needs_label = True put_success = False put_success = True qsize = 0 size = 1 pad_w = 0 pad_h = 0 dilate = 1 param_string = "pooling_convention='full', " flatten_count = 0 output_name = "" type_string = '' param_string = '' skip_layer = False type_string = 'mx.symbol.Convolution' type_string = 'mx.symbol.Deconvolution' type_string = 'mx.symbol.Pooling' type_string = 'mx.symbol.Activation' param_string = "act_type='relu'" param_string = "act_type='tanh'" param_string = "act_type='sigmoid'" type_string = 'mx.symbol.LRN' type_string = 'mx.symbol.FullyConnected' type_string = 'mx.symbol.Dropout' type_string = 'split' type_string = 'mx.symbol.Concat' type_string = 'mx.symbol.Crop' param_string = 'center_crop=True' type_string = 'mx.symbol.BatchNorm' skip_layer = True type_string = 'mx.symbol.LeakyReLU' type_string = 'mx.symbol.broadcast_add' param_string = "" type_string = 'mx.symbol.Reshape' type_string = 'mx.symbol.abs' type_string = 'mx.symbol.transpose' from_name = '' type_string = 'mx.contrib.symbol.MultiBoxDetection' type_string = 'mx.symbol.SoftmaxActivation' param_string = "mode='channel'" type_string = 'mx.symbol.SoftmaxOutput' type_string = 'mx.symbol.Flatten' epsilon = 1e-04 all_done = False t = 1 t = 0 str_chunk = '' more = True more = False epoch_size = 1 loss_type = 'nll_loss' num = 1 max_count = 0 font_scale = 0.5 prefix = 'checkpoint/epoches' sum_losses = 0 len_losses = 0 iter_no = 0 crop_size = 256 total_L = 0.0 nbatch = 0 density = 0 end_of_batch = False end_of_batch = True pos_path = "./data/rt-polaritydata/rt-polarity.pos" neg_path = "./data/rt-polaritydata/rt-polarity.neg" ret = '' ret2 = '' num_tables = 0 output = '' in_table = False in_table = True in_code = False in_code = True ret_status = True err = '' ret_status = False start_offset = 0.1 step = '(-1.0, -1.0)' end = 0 nerr = 0 can_infer_input_type = True can_infer_input_type = False line_format = '{:>20} {:>42} {:>15}' trainable_params = 0 shared_params = 0 params = 0 head = '%(asctime)-15s %(message)s' dtype = 'float' dtype = 'double' num_stages = 3 num_stages = 4 bottle_neck = True bottle_neck = False sections = 0 num_provided_arg_types = 0 num_provided_arg_stypes = 0 provided_req_type_list_len = 0 dry_run = 5 new_vocab = True new_vocab = False p = 0 log_format = ' {0:<40} {1:<40} {2:<8} {3:>10} {4:>10} {5:<1}' mx_name = 'data' style_loss = 0. minibatch_size = 100 num_hidden = 800 total_iter_num = 1000000 teacher_learning_rate = 1E-6 student_learning_rate = 0.0001 teacher_prior = 1 student_prior = 0.1 perturb_deviation = 0.1 num_hidden = 400 total_iter_num = 20000 teacher_learning_rate = 4E-5 perturb_deviation = 0.001 minibatch_size = 1 teacher_noise_precision = 1.0 / 9.0 teacher_noise_precision = 1.0 noise_precision = 1 / 9.0 theta1 = 0 theta2 = 1 sigma2 = 1 mode = 0 non_linearity = 'RELU' non_linearity = 'TANH' non_linearity = 'SIGMOID' non_linearity = 'ELU' non_linearity = 'LEAKYRELU' non_linearity = 'PRELU' border_mode = "valid" stride_height = 1 stride_width = 1 has_bias = True layer_type = 'MAX' is_global = False layer_type = 'AVERAGE' eps = 1e-3 use_global_stats = False fix_gamma = True mode = 'CONCAT' sleep_s = 1 sleep_s = 0 show_shape = False show_shape = True line = '' pre_filter = 0 cur_param = 0 first_connection = '' class_idx = 0 storage_type = 'csr' storage_type = 'row_sparse' denom = 1. ap = 0. bar_len = 24 base_url = 'http://yann.lecun.com/exdb/mnist/' model_prefix = "FCN8s_VGG16" epoch = 19 s = '' source = '' path = 'execinfo.h' col_start = 0 to_reduce = False to_reduce = True accept_num = 0 registry = "mxnet_local" ccache_dir = "/tmp/_mxnet_ccache" container_wait_s = 600 runtime = 'nvidia' ret = 150 ret = 151 ret = 152 bs = 4 actual_num_batch = 0 vs_configuration = 'Release' buf = "" source_exts = '*.mpg' face_predictor_path = './shape_predictor_68_face_landmarks.dat' fail_cnt = 0 mouth_width = 100 mouth_height = 50 horizontal_pad = 0.19 cumulative_loss = 0 lmFactor = 0.01 prNonBlank = 0 is_NDArray_or_list = True is_NDArray_or_list = False steps = 0 best_val = 0.0 default_repo = 'https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/' first_conv = True first_conv = False iter = 0 shape = 1 hash_bucket_size = 1000 dns_dim = 0 update_on_kvstore = True P = 0.01 num_non_zero = 0 num_sample = 0 ntrial = 0 hit = 0. total = 0. match = True num_samples = 0 cudnn_min_eps = 1e-5 trans_a = 0 trans_b = 0 alpha = 1 beta = 1 mode = 'training' mode = 'always' idx = 0 dtype = 'int32' advanced_indices_adjacent = True is_advanced_index = True advanced_indices_adjacent = False is_advanced_index = False need_broadcast = True dim_size = 1 tokens = 0 token = 0 path = "mxnet/cython" subdir = "_cy3" subdir = "_cy2" num_layers = 50 image_shape = '3,224,224' network = 'resnet' num_layers = 101 res = 'res ' arg_format = '' value = '' num_excluded_symbols = 0 num_offline = 0 train_loss_sum = 0.0 test_loss_sum = 0.0 val_train_defined = False val_train_defined = True n_epoch = 0 batch_sum_metric = 0 batch_num_inst = 0 update_on_kvstore = False default_batch = '16' do_reset = True total_num_batch = 0 do_reset = False is_error = False is_error = True npos = 0 graph_input_idx = 0 N = 1000 M = 60 rank_data_url = 'https://raw.githubusercontent.com/Microsoft/LightGBM/master/examples/lambdarank/' cache_match = False cache_match = True nsamples = 100 multi_output = True multi_output = False v = 0.0 total_neg = 0 total_pos = 0 width_bar = 0.1 flat_output = False flat_output = True tree_limit = 0 transform = "identity" transform = "logistic" transform = "squared_loss" transform = "logistic_nlogloss" msg = "Length of features is not equal to the length of shap_values!" internal_open = False internal_open = True total_sent = 0 total_done = 0 total_failed = 0 inc = 50 arr_type = "'numpy.ndarray'>" fname = "sum(SHAP values)" categorical_interaction = False categorical_interaction = True x_jitter = 1 N = 1000000 M = 3 multi_class = False row_height = 0.4 multi_class = True plot_type = "bar" title_length_limit = 11 max_display = 20 color = "coolwarm" max_display = 7 colored_feature = True nbins = 100 layer = 0 num_x_points = 200 colored_feature = False trailing_pos = 0 leading_pos = 0 running_sum = 0 back_fill = 0 width = 0.8 _name = "AgentImportFailed" last_debug = 0 saved_as_dict = False saved_as_dict = True mode = "w" mode = "w+" image_size = 32 depth = 3 label_bytes = 1 label_offset = 0 label_offset = 1 function_name = "__init__" sequences_per_minibatch = 1 can_overcommit = False log = "Constructed {} input and {} output channels " anything_published = False max_num_lines_to_read = 100 anything_published = True num_consecutive_messages_received = 0 error_message = "Perhaps you called ray.init twice by accident?" nil_actor_counter = 0 next_title = "ray_worker" seed = 123 num_timesteps_so_far = 0 memory_limit_filename = "/sys/fs/cgroup/memory/memory.limit_in_bytes" bytes_in_kilobyte = 1024 progress = 0 sort_key = "accuracy" sort_key = "episode_reward" query = "XREAD BLOCK " rate = 1 seq_len = 0 seq_base = 0 i = 1 label = "fc_out" node_ip_address = "127.0.0.1" use_valgrind = True use_valgrind_profiler = True use_perftools_profiler = True use_tmux = True use_gdb = True proc_gpus_path = "/proc/driver/nvidia/gpus" num_retries = 1 redis_client_buffer = 32 port = 8080 java_worker_command = "" object_manager_port = 0 node_manager_port = 0 plasma_directory = "/tmp" plasma_directory = "/dev/shm" k = "Name" running_add = 0 success = False retry = True retry = False out = "Using HyperBand: " num_deleted = 0 num_task_keys_deleted = 0 num_object_keys_deleted = 0 num_object_location_keys_deleted = 0 has_kwargs_param = False has_kwonly_param = False has_kwargs_param = True has_kwonly_param = True key_found = False key_found = True already_configured = True role_exists = False already_configured = False role_exists = True num_yielded = 0 remote_key_path = "~/ray_bootstrap_key.pem" monitor_str = "tail -n 100 -f /tmp/ray/session_*/logs/monitor*" modifiers = "" cmd = "tmux new" cmd = "tmux attach || tmux new" cmd = "screen -L" cmd = "screen -L -xRR" component_type = "worker" component_type = "driver" _log_sync_warned = True name_key = "resnet_v1" shards = 1 group_index = 0 cur_size = 0 class_name = "" warning_sent = False warning_sent = True all_done = True hit_horizon = False flatc = '' numpy_exists = True numpy_exists = False off = 0 msg = "flatbuffers: cannot grow buffer beyond 2 gigabytes" newSize = 1 msg = "flatbuffers: Offset arithmetic error." retval = "" use_system = False cert_reqs = 'CERT_REQUIRED' start_text = "" spinner_name = "bouncingBar" combine_stderr = False errors = "strict" has_ipv6 = False has_ipv6 = True config_dir_name = 'config' num_called_num = False have_plural = False have_plural = True encoding = "utf-8" can_use_original = True can_use_updated = True has_mismatch = False can_use_original = False has_mismatch = True read_count = 0 sent = 0 length = 0 status = 0 clean_exit = False clean_exit = True flush_decoder = False flush_decoder = True cache_content = False text = "" token = 'block_begin' token = 'block_end' use_pep517 = True backend = "setuptools.build_meta:__legacy__" msg = "" msg = " It does exist." marker_sep = '; ' marker_sep = ';' add_msg = "It looks like a path." add_msg = "= is not a valid operator. Did you mean == ?" add_msg = "" results_printed = False results_printed = True pop_tag = True pop_tag = False path = "/" freshness_lifetime = 0 no_store = False no_store = True name = "sha256" rv = '' broken = False broken = True not_python = True extras_string = "" indent = 0 arg = '' state_basic = 0 state_esc = 1 state_singlequote = 2 state_doublequote = 3 state_whitespace = 4 result = '0.0.0' prefix = '0.0.0' quote_mode = "always" replaced = False replaced = True removed = False removed = True include_index = True exeness = False using_socks_proxy = False prefix = ' or' max_prober_confidence = 0.0 url = "" total_length = 0 rv = True rv = False cause = 'unknown' cause = 'too many redirects' from_cache = True hasher = 'md5' blocksize = 8192 read = 0 blocknum = 0 quoted = False quoted = True incomplete = '' append = True stale = True result = 0 had_default = False was_kw_only = False was_kw_only = True had_default = True first = True first = False maybe_self = "self" maybe_self = "" init_hash_cache = "self.%s = %s" init_hash_cache = "_setattr('%s', %s)" init_hash_cache = "_inst_dict['%s'] = %s" tmpl = "_setattr('%(attr_name)s', %(c)s(%(value_var)s))" tmpl = "_inst_dict['%(attr_name)s'] = %(c)s(%(value_var)s)" weakref_inherited = False weakref_inherited = True rawmode = "" initial_skip = 0 initial_skip = 1 filename = '<unknown>' autodelete_unpacked = True autodelete_unpacked = False msg = "EntryPoint must be in 'name=module:attrs [extras]' format" names = 'project_name version py_version platform location precedence' has_yaspin = True spinner_name = "" use_yaspin = True start_text = "Running..." has_yaspin = False errmsg = 'getecho() may not be called on this platform' compatible = True CHARS = '0123456789abcdefghijklmnopqrstuvwxyz' sign = 1 base = 2 base = 8 base = 16 time_only = False time_only = True zero = False width = '' zero = True precision = '' fancy = True radix = 10 radix = 16 char = "\uFFFD" problems = False problems = True missed = True in_tag = False prev = 0 in_tag = True new_url = "" marker_sep = ";" marker_sep = "; " vcs_start = "{0}+" include = True nested_constraint = False nested_constraint = True op = "==" op = "===" version = '' filename = '<template>' extra = '' has_c_utf8 = False fs_enc = 'ascii' has_c_utf8 = True _initialized = True from_symbols = '&><"\'' listAllMatches=True splits = 0 binary_preference = 0 binary_preference = 1 best_installed = False best_installed = True support_this_python = True event_count = 0 path = '/' content_type = 'application/json' content_type = 'application/x-www-form-urlencoded' http_error_msg = '' user_option_part = "Consider using the `--user` option" permissions_part = "Check the permissions" release_this_conn = True method = 'GET' simple_shebang = True max_shebang_length = 512 max_shebang_length = 127 implementation_version = "0" implementation_name = 'cpython' msg = '%s is already registered for "%s"' label = 'any' valid_counter = 0 pos = 1 do_escape = False do_escape = True current = '' suffix = ".fish" command = "source" suffix = ".csh" suffix = "" command = "." buildver = '' is_pure = 'false' is_pure = 'true' USING_DEFAULT_PYTHON = False system = True bare = True ignore_hashes = True global_search = True error_msg = "Load expects a list to contain filenames only." openarr = 0 openstring = False openstrchar = "" multilinestr = False arrayoftables = False beginline = True keygroup = False dottedkey = False keyname = 0 multilinestr = "" multibackslash = False k = 1 oddbackslash = False tripquote = False openstrchar = "'" openstrchar = '"' beginline = False arrayoftables = True splitstr = ']]' splitstr = ']' keyname = 2 keygroup = True keyname = 1 tripquote = True dottedkey = True openstring = True msg = 'Netmask pattern %r mixes zeroes & ones' _min_parts = 3 parts_lo = 0 parts_skipped = 0 ip_int = 0 msg = "Expected at most %d other parts with '::' in %r" msg = "Exactly %d parts expected without '::' in %r" msg = "Leading ':' only permitted as part of '::' in %r" msg = "Trailing ':' only permitted as part of '::' in %r" msg = "At most 4 characters permitted in %r" best_doublecolon_len = 0 doublecolon_len = 0 modified_something = False timeout = 0.001 default_warning_message = "Unable to remove file due to permissions restriction: {!r}" expired = 0.0 setup_py = 'setup.py' suffix = '.distlib' usable = True usable = False msg = """invalid glob %r: recursive glob "**" must be used alone""" msg = """invalid glob %r: mismatching set marker '{' or '}'""" level = "DEBUG" root_level = "DEBUG" additional_log_file = "/dev/null" level = "WARNING" level = "ERROR" level = "CRITICAL" level = "INFO" prefix = '' any_prefix_is_slash = False any_prefix_is_slash = True n = 0 BUFSIZE = 16 * 1024 pos = 386 encoding = "utf8" value = 0 linkname = "" changed_values = False changed_values = True outdent_later = False outdent_later = True close = 0 skip = True skip = False pattern_re = '' err = 'create_cookie() got unexpected keyword arguments: %s' time_template = '%a, %d-%b-%Y %H:%M:%S GMT' line = u'' output = u"" implementation_version = 'Unknown' columns = 0 lines = 0 style = "NORMAL" style = "BRIGHT" comment = "" comment_ws = "" trail = "" dotted = False dotted = True is_aot = False missing_table = False is_aot = True missing_table = True chars = 8 chars = 4 url = '' type = "EndTag" is_dir = False walk_into = True is_symlink = False pip_cmd = "python -m pip" pip_cmd = "pip" pyimpl = 'pp' pyimpl = 'jy' pyimpl = 'ip' pyimpl = 'cp' result = "linux_i686" machine = "i386" machine = "ppc" items_to_strip = "\"' " safe_with_percent = "!#$%&'()*+,/:;=?@[]~" safe_without_percent = "!#$&'()*+,/:;=?@[]~" bypass = False kwarg_workaround = False kwarg_workaround = True func_name = 'get_or_select_template' skip_event_yield = False func_name = 'get_template' func_name = 'select_template' skip_event_yield = True defaults_seen = 0 template = "{arg} = {processor}({func}, '{arg}', {arg})" successful = True successful = False missing = 0 sharpe = 0.0 assets_is_scalar = False assets_is_scalar = True ffill_data_frequency = 'minute' ffill_data_frequency = 'daily' actual_repr = 'scalar' stop_reached = False limit_reached = False sl_stop_reached = False order_type = 0 sl_stop_reached = True limit_reached = True stop_reached = True share_class_symbol = '' version_from_table = 0 total_rows = 0 minutely_emission = False total_leftover_cash = 0 net_cash_payment = 0.0 returns = 0.0 field_hit = False field_hit = True unlock_url = 'http://weixin.sogou.com/antispider/thank.php' unlock_url = 'https://mp.weixin.qq.com/mp/verifycode' interation_image = 458754 interation_video = 458756 ft = '' et = '' interation = '' description_prefix = "" wibble = 100 mapsize = 512 size = 0 msg = "You must download the dataset files manually and place them in: " ndims = 2 TF_PATCH = "tf1_12" TF_PATCH = "tf1_13" TF_PATCH = "tf2" encoding_format = "png" encoding_format = "jpeg" version_str = '0.0.1' total_num_examples = 0 title = "" version = "0.1.0" failed_parse = False failed_parse = True num_chars = 0 skip_single_token = False skip_next = False skip_next = True num_skipped = 0 root_url = "http://images.cocodataset.org/" annotation_skipped = 0 instance_filename = "instances_{}.json" instance_filename = "image_info_{}.json" shard_suffix = "%05d-of-%05d" size_mb = 0 next_is_highlight = False next_is_highlight = True supress_regex = True time_per_request = 0 entropy = 0 editor = 'nano' res=1 unit = 1 frozen = 1 tax_fee = 0 order = False start_date = '1990-01-01' res = False res = True shortName = "" a = 100 cont = True cont = False limitUp = 0 limitDown = 0 null = 'none' order_model = 4 order_model = 0 month = 1 start_time = "2015-01-01 09:30:00" level = 1 frequence = 9 frequence = 5 frequence = 6 frequence = 10 frequence = 11 type_ = '' lens = 20800 pt = 0 stdout = "" ZERO = 0 frequence = '1min' frequence = '5min' frequence = '15min' frequence = '30min' frequence = '60min' start_time = '2015-01-01' start_time = '1990-01-01' start_time = '2009-01-01' start_date = '2001-01-01' start = '1990-01-01' n_statement = '1.0' previous_statement_search_text = '' download = 0 hour = 0 minute = 0 convention = 'am' interval = 3 month_start = 9 month_start = 1 message = "Unknown extension '{}', supports {}." num_activation_groups = 1 width = 1 d = 0 pyramid = 0 S = 0 accum = 0 message = "Using inferred loader '%s' due to passed file extension '%s'." message = "Could not load resource %s as image. Supported extensions: %s" message = "No domain specified, normalizing from measured (~%.2f, ~%.2f)" message = "Clipping domain from (~{:.2f}, ~{:.2f}) to (~{:.2f}, ~{:.2f})." message = "Unsupported mode '%s', should be one of '%s'." s = '<div style="display: flex; flex-direction: row;">' cache = True UNICODE_WIDE_CHAR_TYPE = 'WFA' width = 0 denies = 0 allows = 0 perm_type = 'member' perm_type = 'role' status = 'online' status = 'invisible' cancelled = False cancelled = True auto_reload = False auto_reload = True proto = "http" proto = "https" status = 206 url = "unknown" response_message = "Exception occurred while handling uri: %s" start_shutdown = 0 keep_alive = False content_type = "text/plain" content_charset = "utf-8" line_index = 2 line_end_index = 0 pattern = "string" is_static = False is_static = True route_found = False needs_float = False needs_float = True mode = "module" mode = "script" encoding = "utf-16" encoding = "utf-8-sig" plural = "unknown" _use_gettext = True full_format = True k = "max-age" message = "write() only accepts bytes, unicode, and dict objects" score = 1.0 version = 1 base = "" chunk_size = 64 * 1024 max_len = 30 proto_len = 0 new_buf = True flags = 0 code = 1000 file_name = "" value = "true" num_restarts = 0 max_restarts = 100 action = 0 available = 1 start_pos = 0 rsv = 0 mask_bit = 0 domain = "" req_path = "/" found_time = False found_day = False found_month = False found_year = False day = 0 month = 0 year = 0 found_time = True found_day = True found_month = True found_year = True need_separator = False need_separator = True ct = 'text/plain' ct = 'text/html' fulltype = '*/*' connector_owner = False connector_owner = True upgrade = False chunked = False chunked = True close_conn = True close_conn = False upgrade = True reload = False epoch_loss = 0.0 flag_break = True flag_arrive = True flag_break = False flag_arrive = False cnt_try = 0 cnt = 0 EMBEDDING_DIM = 300 tokenized_sent = 0 expected_version = '1.1' _completed_num = 0 msg = 'Result of Assessor.assess_trial must be an object of AssessResult, not %s' output_node_id = 0 package = '' annotated = False test_acc = 0.0 experiment_information = "" t = 1.0 alpha = 0.9 bestacc = 0 patience = 5 patience_increase = 2 improvement_threshold = 0.995 fmt = '[%(asctime)s] %(levelname)s (%(name)s/%(threadName)s) %(message)s' fmt = 'squad' history_sum = 0 temp_id = 0 new_father_id = 0 logger_file_path = 'dispatcher.log' bw_estimation = 'normal_reference' retry_count = 5 node_command = 'node' err_message = '' log_level = 'debug' var = 0 pattern = r'(?P<head>.+)://(?P<host>.+):(?P<path>.*)' sigma = 0 budget_exist_flag = False budget_exist_flag = True budget_allocated = 0 validate = False validate = True train_loss = 0 api = "http://yh.ez.shidenggui.com:5000/yh_client" agent = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.11; rv:43.0) Gecko/20100101 Firefox/43.0" home_page_url = "https://xueqiu.com" is_have = False is_have = True cifar_foldername = 'cifar-10-batches-py' cifar_foldername = 'cifar-100-python' data_format = 'NHWC' data_format = 'channels_first' nf = 64 shape_err = "Use of BatchQueueInput requires inputs to have fully-defined " dir_structure = 'train' dir_structure = 'original' rate = 0.5 cmd = "protoc --version" INTERVAL = 200 GRAPH_ARG_NAME = '__IMPOSSIBLE_NAME_FOR_YOU__' name = 'tensorpack_viz_window' viz = True suffix = '-summary' placeholder = 0. delta = 1.0 / 9 placeholder = 0.5 flush_experience = True flush_experience = False total_bytes = 0 ele = 0 shape = '<unknown>' eps = 1e-10 list_split = 0 ascending = False expecting = "pad (ffill) or backfill (bfill)" axis = "columns" inplace = True ndim = 0 ndim = 2 read_from_pandas = True read_from_pandas = False row_position_counter = 0 col_position_counter = 0 attempts = 10 unsuccesful_mutations = 0 operator_count = 0 this_class_sensitivity = 0. this_class_specificity = 0. optype = "Classifier" optype = "Transformer" optype = "Selector" optype = "Regressor" msg = "'use_dask' requires the optional dask and dask-ml depedencies." data_file_path = 'PATH/TO/DATA/FILE' mutations_count = 0 num_responses = 0 num_retryable_responses = 0 parameter_type = "BOOL" parameter_type = "INT64" parameter_type = "FLOAT64" parameter_type = "NUMERIC" parameter_type = "STRING" parameter_type = "BYTES" parameter_type = "DATE" parameter_type = "TIME" save_to_backend = True content_type = "application/json" key = "resource.type" term = '{key} = starts_with("{value}")' term = '{key} = ends_with("{value}")' term = "{key} > {value}" term = "{key} >= {value}" term = "{key} < {value}" term = "{key} <= {value}" term = '{key} = "{value}"' name = "timestamp" partial_success = False mutation_size = 0 _has_snapshot_cursor = False _has_snapshot_cursor = True version = "v2" micros = 0 nanos = 0 single_value = False single_value = True description = "Downloading" unit = "rows" key = "read_timestamp" key = "min_read_timestamp" key = "max_staleness" key = "exact_staleness" key = "strong" value = True ua = "" FILTER = "logName:log_name AND textPayload:simple" DESCRIPTION = "Robots all up in your server" FILTER = "logName:apache-access AND textPayload:robot" UPDATED_FILTER = "textPayload:robot" UPDATED_DESCRIPTION = "Danger, Will Robinson!" FILTER = "textPayload:robot" prefix = "X-Goog-Copy-Source-Encryption-" prefix = "X-Goog-Encryption-" key = "start_qualifier_closed" key = "start_qualifier_open" key = "end_qualifier_closed" key = "end_qualifier_open" key = "start_value_closed" key = "start_value_open" key = "end_value_closed" key = "end_value_open" path = "/entries:list" start_key_key = "start_key_open"