SYMBOL INDEX (106 symbols across 9 files)

FILE: a00_common_functions.py
  function save_in_file (line 20) | def save_in_file(arr, file_name):
  function load_from_file (line 24) | def load_from_file(file_name):
  function show_image (line 28) | def show_image(im, name='image'):
  function show_resized_image (line 34) | def show_resized_image(P, w=1000, h=1000):
  function relu_1 (line 39) | def relu_1(x):
  function save_history (line 44) | def save_history(history, path, columns=('loss', 'val_loss')):
  function get_model (line 54) | def get_model(weights_path):
  function get_model_memory_usage (line 62) | def get_model_memory_usage(batch_size, model):

FILE: a01_oid_utils.py
  function get_model_memory_usage (line 21) | def get_model_memory_usage(batch_size, model):
  function get_description_for_labels (line 48) | def get_description_for_labels():
  function random_intensity_change (line 59) | def random_intensity_change(img, max_change):
  function random_rotate (line 69) | def random_rotate(image, max_angle):
  function read_single_image (line 79) | def read_single_image(path):
  function read_image_bgr_fast (line 104) | def read_image_bgr_fast(path):
  function prepare_training_csv (line 109) | def prepare_training_csv(type, true_labels_enc, output_path, side_size=1...
  function check_validation_set (line 143) | def check_validation_set(input_csv):
  function check_train_set (line 161) | def check_train_set(input_csv):
  function get_class_labels (line 179) | def get_class_labels(true_labels):

FILE: r02_train_mobilenet.py
  function strong_aug (line 48) | def strong_aug(p=.5):
  function process_single_item (line 85) | def process_single_item(id, box_size, validation=True):
  function batch_generator (line 114) | def batch_generator(X_train, Y_train, batch_size, input_size, prep_input...
  function evaluate_generator (line 144) | def evaluate_generator(X_test, Y_test, batch_size, input_size, prep_input):
  function load_train_valid_data (line 174) | def load_train_valid_data(train_csv, valid_csv):
  function train_mobile_net_v1 (line 185) | def train_mobile_net_v1(input_size, train_csv, valid_csv, type):
  function evaluate_model (line 265) | def evaluate_model(model_path, input_size, train_csv, valid_csv):

FILE: r03_mobilenet_v1_reduce_and_scale_model.py
  function preproc_input_mathmodel (line 32) | def preproc_input_mathmodel(x):
  function rescale_weights (line 38) | def rescale_weights(model, layer_num, coeff):
  function rescale_weights_with_bias (line 44) | def rescale_weights_with_bias(model, layer_num, coeff, current_scale):
  function rescale_only_bias (line 52) | def rescale_only_bias(model, layer_num, coeff, current_scale):
  function rescale_batch_norm_weights_initital_v1 (line 60) | def rescale_batch_norm_weights_initital_v1(model, layer_num, coeff, curr...
  function rescale_batch_norm_weights_initital (line 76) | def rescale_batch_norm_weights_initital(model, layer_num, coeff, current...
  function rescale_dense_weights (line 85) | def rescale_dense_weights(model, layer_num, current_scale, coeff):
  function is_next_relu6 (line 99) | def is_next_relu6(model, layer_id):
  function replace_intermediate_layer_in_keras (line 112) | def replace_intermediate_layer_in_keras(model, layer_id, new_layer):
  function get_min_max_for_model (line 128) | def get_min_max_for_model(model, img_list):
  function load_oid_data (line 222) | def load_oid_data(type):
  function process_single_item (line 233) | def process_single_item(id, box_size):
  function check_results_are_the_same (line 239) | def check_results_are_the_same(model_path1, model_path2, img_list):

FILE: r04_find_optimal_bit_for_weights.py
  function my_convolve (line 31) | def my_convolve(input, kernel):
  function my_convolve_fixed_point (line 44) | def my_convolve_fixed_point(input, kernel, bit):
  function preprocess_forward (line 57) | def preprocess_forward(arr, val):
  function convert_to_fix_point (line 63) | def convert_to_fix_point(arr1, bit):
  function from_fix_point_to_float (line 74) | def from_fix_point_to_float(arr, bit):
  function compare_outputs (line 78) | def compare_outputs(s1, s2, debug_info=True):
  function print_first_pixel_detailed_calculation_dense (line 91) | def print_first_pixel_detailed_calculation_dense(previous_layer_output, ...
  function print_first_pixel_detailed_calculation (line 104) | def print_first_pixel_detailed_calculation(previous_layer_output, wgt_bi...
  function mmZeroPadding2D_floating_point (line 135) | def mmZeroPadding2D_floating_point(layer, img):
  function mmZeroPadding2D_fixed_point (line 156) | def mmZeroPadding2D_fixed_point(layer, img):
  function run_TF_Conv2D (line 177) | def run_TF_Conv2D(img, w, b, strides, padding, type='float'):
  function run_TF_Depthwise_Conv2D (line 195) | def run_TF_Depthwise_Conv2D(img, w, b, strides, padding, type='float'):
  function mmConv2D_floating_point (line 213) | def mmConv2D_floating_point(layer, img, debug_info):
  function mmConv2D_fixed_point (line 295) | def mmConv2D_fixed_point(layer, img, bit_precizion, bit_precizion_weight...
  function mmGlobalAveragePooling2D_floating_point (line 390) | def mmGlobalAveragePooling2D_floating_point(img):
  function mmGlobalAveragePooling2D_fixed_point (line 399) | def mmGlobalAveragePooling2D_fixed_point(img):
  function mmActivation_floating_point (line 410) | def mmActivation_floating_point(layer, img, one_value=1.0, debug_info=Fa...
  function mmActivation_fixed_point (line 424) | def mmActivation_fixed_point(layer, img, bit_precizion, debug_info=False):
  function mmReLU_floating_point (line 438) | def mmReLU_floating_point(layer, img, one_value=1.0, debug_info=False):
  function mmReLU_fixed_point (line 452) | def mmReLU_fixed_point(layer, img, bit_precizion, debug_info=False):
  function mmDepthwiseConv2D_floating_point (line 466) | def mmDepthwiseConv2D_floating_point(layer, img, debug_info):
  function mmDepthwiseConv2D_fixed_point (line 529) | def mmDepthwiseConv2D_fixed_point(layer, img, bit_precizion, bit_precizi...
  function mmDense_floating_point (line 601) | def mmDense_floating_point(layer, img, debug_info):
  function mmDense_fixed_point (line 642) | def mmDense_fixed_point(layer, img, bit_precizion, bit_precizion_weights...
  function go_mat_model (line 692) | def go_mat_model(model, images, bit_precizion, bit_precizion_weights, bi...
  function get_error_rate (line 766) | def get_error_rate(a1, a2):
  function preproc_input_mathmodel (line 775) | def preproc_input_mathmodel(x):
  function load_oid_data_optimal (line 781) | def load_oid_data_optimal(type):
  function get_image_set (line 788) | def get_image_set(type, image_limit, preproc_type='keras'):
  function find_conv_overflow_bit_values (line 823) | def find_conv_overflow_bit_values(model):
  function get_optimal_bit_for_weights (line 853) | def get_optimal_bit_for_weights(type, model_path, image_limit, acceptabl...

FILE: r05_gen_weights_in_verilog_format.py
  function my_convolve (line 26) | def my_convolve(input, kernel):
  function my_convolve_fixed_point (line 39) | def my_convolve_fixed_point(input, kernel, bit):
  function preprocess_forward (line 52) | def preprocess_forward(arr, val):
  function convert_to_fix_point (line 58) | def convert_to_fix_point(arr1, bit):
  function from_fix_point_to_float (line 69) | def from_fix_point_to_float(arr, bit):
  function compare_outputs (line 73) | def compare_outputs(s1, s2, debug_info=True):
  function dump_memory_structure_conv (line 86) | def dump_memory_structure_conv(arr, out_file):
  function dump_memory_structure_dense (line 99) | def dump_memory_structure_dense(arr, out_file):
  function print_first_pixel_detailed_calculation_dense (line 111) | def print_first_pixel_detailed_calculation_dense(previous_layer_output, ...
  function print_first_pixel_detailed_calculation (line 124) | def print_first_pixel_detailed_calculation(previous_layer_output, wgt_bi...
  function convert_to_normalized_form (line 155) | def convert_to_normalized_form(value, precision, required_precision=None):
  function convert_to_normalized_form_array (line 176) | def convert_to_normalized_form_array(value, precision):
  function convert_to_normalized_form_v2 (line 182) | def convert_to_normalized_form_v2(value, precision):
  function get_shape_string (line 199) | def get_shape_string(w):
  function gen_convolution_weights (line 206) | def gen_convolution_weights(level_id, layer, bit_precizion, weight_bit_p...
  function gen_depthwise_convolution_weights (line 307) | def gen_depthwise_convolution_weights(level_id, layer, bit_precizion, we...
  function gen_dense_weights (line 403) | def gen_dense_weights(level_id, layer, bit_precizion, out_weights):
  function generate_weights_for_layers (line 455) | def generate_weights_for_layers(model, bp, weight_bit_precision, bias_bi...

FILE: r06_generate_debug_data.py
  function convert_to_normalized_form_v2 (line 24) | def convert_to_normalized_form_v2(value, precision):
  function store_layer_result (line 41) | def store_layer_result(level_id, layer, layer_type, bp, res):
  function print_convolution_detailed_first_pixel_calculation (line 92) | def print_convolution_detailed_first_pixel_calculation(level_id, layer, ...
  function print_depthwise_conv_detailed_first_pixel_calculation (line 168) | def print_depthwise_conv_detailed_first_pixel_calculation(level_id, laye...
  function print_dense_detailed_first_pixel_calculation (line 241) | def print_dense_detailed_first_pixel_calculation(level_id, layer, img, i...
  function get_filters_size (line 285) | def get_filters_size(arr):
  function generate_layer_results (line 290) | def generate_layer_results(model, images, image_bit_precizion, weight_bi...
  function get_debug_image (line 356) | def get_debug_image():
  function generate_layer_results_for_image (line 366) | def generate_layer_results_for_image(type, model, image_bit_precision, w...

FILE: r07_generate_verilog_for_mobilenet.py
  function addressRAM (line 13) | def addressRAM(directory, steps_count, max_address_value):
  function border (line 441) | def border(directory, razmer):
  function conv_block (line 471) | def conv_block(directory,razmer):
  function conv_TOP (line 516) | def conv_TOP(directory, razmer, max_conv_input_size, max_conv_output_siz...
  function dense (line 1054) | def dense(directory, in_dense_razmer, out_dense_razmer, num_conv, sizeI,...
  function RAM (line 1274) | def RAM(directory, max_weights_per_layer, num_conv):
  function RAMtoMEM (line 1336) | def RAMtoMEM(directory, max_address_value, steps_count, in_dense_razmer,...
  function result (line 1516) | def result(directory,output_neurons_count,num_conv):
  function TOP (line 1571) | def TOP(directory, sizeI, sizeW, sizeB, razmer, max_address_value, outpu...

FILE: r08_generate_weights_file_for_FPGA.py
  function load_cache_file (line 4) | def load_cache_file(f):