Lines Matching refs:node
46 def _zero_flops(graph, node):
48 del graph, node # graph and node are unused
64 def _unary_op_flops(graph, node, ops_per_element=1):
66 in_shape = graph_util.tensor_shape_from_node_def_name(graph, node.input[0])
72 def _reciprocal_flops(graph, node):
74 return _unary_op_flops(graph, node)
78 def _square_flops(graph, node):
80 return _unary_op_flops(graph, node)
84 def _rsqrt_flops(graph, node):
87 return _unary_op_flops(graph, node, ops_per_element=2)
91 def _log_flops(graph, node):
93 return _unary_op_flops(graph, node)
97 def _neg_flops(graph, node):
99 return _unary_op_flops(graph, node)
103 def _assign_sub_flops(graph, node):
105 return _unary_op_flops(graph, node)
109 def _assign_add_flops(graph, node):
111 return _unary_op_flops(graph, node)
115 def _l2_loss_flops(graph, node):
117 in_shape = graph_util.tensor_shape_from_node_def_name(graph, node.input[0])
125 def _softmax_flops(graph, node):
133 return _unary_op_flops(graph, node, ops_per_element=5)
140 def _binary_per_element_op_flops(graph, node, ops_per_element=1):
142 out_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
148 def _add_flops(graph, node):
150 return _binary_per_element_op_flops(graph, node)
154 def _sub_flops(graph, node):
156 return _binary_per_element_op_flops(graph, node)
160 def _mul_flops(graph, node):
162 return _binary_per_element_op_flops(graph, node)
166 def _real_div_flops(graph, node):
168 return _binary_per_element_op_flops(graph, node)
172 def _maximum_flops(graph, node):
174 return _binary_per_element_op_flops(graph, node)
178 def _minimum_flops(graph, node):
180 return _binary_per_element_op_flops(graph, node)
184 def _pow_flops(graph, node):
186 return _binary_per_element_op_flops(graph, node)
190 def _rsqrt_grad_flops(graph, node):
192 return _binary_per_element_op_flops(graph, node, ops_per_element=4)
196 def _greater_equal_flops(graph, node):
198 return _binary_per_element_op_flops(graph, node)
202 def _greater_flops(graph, node):
204 return _binary_per_element_op_flops(graph, node)
208 def _less_equal_flops(graph, node):
210 return _binary_per_element_op_flops(graph, node)
214 def _less_flops(graph, node):
216 return _binary_per_element_op_flops(graph, node)
220 def _equal_flops(graph, node):
222 return _binary_per_element_op_flops(graph, node)
226 def _not_equal_flops(graph, node):
228 return _binary_per_element_op_flops(graph, node)
232 def _squared_difference_flops(graph, node):
234 return _binary_per_element_op_flops(graph, node, ops_per_element=2)
241 def _reduction_op_flops(graph, node, reduce_flops=1, finalize_flops=0):
243 in_shape = graph_util.tensor_shape_from_node_def_name(graph, node.input[0])
245 out_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
253 def _mean_flops(graph, node):
256 return _reduction_op_flops(graph, node, reduce_flops=1, finalize_flops=1)
260 def _sum_flops(graph, node):
263 return _reduction_op_flops(graph, node, reduce_flops=1, finalize_flops=0)
267 def _arg_max_flops(graph, node):
270 return _reduction_op_flops(graph, node, reduce_flops=1, finalize_flops=0)
274 def _arg_min_flops(graph, node):
277 return _reduction_op_flops(graph, node, reduce_flops=1, finalize_flops=0)
281 def _bias_add_grad_flops(graph, node):
285 return _reduction_op_flops(graph, node, reduce_flops=1, finalize_flops=0)
293 def _verify_conv_data_format(node):
296 if node.attr["data_format"].s != b"NHWC":
300 def _pool_flops(graph, node):
303 _verify_conv_data_format(node)
317 out_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
319 kernel_shape = list(node.attr["ksize"].list.i)
325 def _avg_pool_flops(graph, node):
327 return _pool_flops(graph, node)
331 def _max_pool_flops(graph, node):
333 return _pool_flops(graph, node)
337 def _avg_pool_grad_flops(graph, node):
339 _verify_conv_data_format(node)
342 node.input[1])
344 kernel_shape = list(node.attr["ksize"].list.i)
354 def _max_pool_grad_flops(graph, node):
356 _verify_conv_data_format(node)
372 kernel_shape = list(node.attr["ksize"].list.i)
375 node.input[1])
382 def _conv_2d_backprop_input_flops(graph, node):
396 _verify_conv_data_format(node)
398 out_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
402 node.input[1])
405 strides_shape = list(node.attr["strides"].list.i)
414 def _conv_2d_backprop_filter_flops(graph, node):
420 _verify_conv_data_format(node)
422 image_shape = graph_util.tensor_shape_from_node_def_name(graph, node.input[0])
425 kernel_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
428 strides_shape = list(node.attr["strides"].list.i)
441 def _add_n_flops(graph, node):
443 if not node.input:
444 return _zero_flops(graph, node)
445 in_shape = graph_util.tensor_shape_from_node_def_name(graph, node.input[0])
447 return ops.OpStats("flops", in_shape.num_elements() * (len(node.input) - 1))
