import numpy as np from deepmd.env import tf from collections import defaultdict from deepmd.TabInter import TabInter from deepmd.common import ClassArg from deepmd.RunOptions import global_tf_float_precision from deepmd.RunOptions import global_np_float_precision from deepmd.RunOptions import global_ener_float_precision from deepmd.RunOptions import global_cvt_2_tf_float from deepmd.RunOptions import global_cvt_2_ener_float module_path = os.path.dirname(os.path.realpath(__file__)) + "/" assert (os.path.isfile(module_path + "libop_abi.so")), "op module does not exist" op_module = tf.load_op_library(module_path + "libop_abi.so") class Model(): model_type = 'ener' def __init__(self, jdata, descrpt, fitting): self.descrpt = descrpt self.rcut = self.descrpt.get_rcut() self.ntypes = self.descrpt.get_ntypes() # fitting self.fitting = fitting self.numb_fparam = self.fitting.get_numb_fparam() args = ClassArg()\ .add('type_map', list, default = []) \
import os,sys import numpy as np from deepmd.env import tf from tensorflow.python.framework import ops if platform.system() == "Windows": ext = "dll" elif platform.system() == "Darwin": ext = "dylib" else: ext = "so" module_path = os.path.dirname(os.path.realpath(__file__)) assert (os.path.isfile (os.path.join(module_path, "libop_abi.{}".format(ext)))), "op module does not exist" op_module = tf.load_op_library(os.path.join(module_path, "libop_abi.{}".format(ext))) class DeepEval(): """ common methods for DeepPot, DeepWFC, DeepPolar, ... """ def __init__(self, model_file) : model_file = model_file graph = self.load_graph (model_file) t_mt = graph.get_tensor_by_name('load/model_attr/model_type:0') sess = tf.Session (graph = graph) [mt] = sess.run([t_mt], feed_dict = {}) self.model_type = mt.decode('utf-8') def load_graph(self,
dir = os.path.dirname(os.path.realpath(__file__)) from tensorflow.python.framework import ops # load force module if platform.system() == "Windows": ext = "dll" elif platform.system() == "Darwin": ext = "dylib" else: ext = "so" module_path = os.path.dirname(os.path.realpath(__file__)) + "/../" assert (os.path.isfile(module_path + "deepmd/libop_abi.{}".format(ext)) ), "force module does not exist" op_module = tf.load_op_library(module_path + "deepmd/libop_abi.{}".format(ext)) # load grad of force module sys.path.append(module_path) import deepmd._prod_force_grad import deepmd._prod_virial_grad import deepmd._prod_force_se_a_grad import deepmd._prod_virial_se_a_grad import deepmd._prod_force_se_r_grad import deepmd._prod_virial_se_r_grad import deepmd._soft_min_force_grad import deepmd._soft_min_virial_grad def _make_node_names(model_type=None): if model_type == 'ener':
#!/usr/bin/env python3 import os, sys import numpy as np from deepmd.env import tf from tensorflow.python.framework import ops module_path = os.path.dirname(os.path.realpath(__file__)) assert (os.path.isfile(os.path.join( module_path, "libop_abi.so"))), "op module does not exist" op_module = tf.load_op_library(os.path.join(module_path, "libop_abi.so")) class DeepEval(): """ common methods for DeepPot, DeepWFC, DeepPolar, ... """ def __init__(self, model_file): model_file = model_file graph = self.load_graph(model_file) t_mt = graph.get_tensor_by_name('load/model_attr/model_type:0') sess = tf.Session(graph=graph) [mt] = sess.run([t_mt], feed_dict={}) self.model_type = mt.decode('utf-8') def load_graph(self, frozen_graph_filename, prefix='load'): # We load the protobuf file from the disk and parse it to retrieve the # unserialized graph_def with tf.gfile.GFile(frozen_graph_filename, "rb") as f: graph_def = tf.GraphDef()