Merge pull request #5 from deepmodeling/devel

Devel update

deepmd/descriptor/__init__.py

@@ -1,9 +1,9 @@
-from .hybrid    import DescrptHybrid
-from .se_a      import DescrptSeA
-from .se_r      import DescrptSeR
-from .se_ar     import DescrptSeAR
-from .se_a_t    import DescrptSeAT
-from .se_a_ebd  import DescrptSeAEbd
-from .se_a_ef   import DescrptSeAEf
-from .se_a_ef   import DescrptSeAEfLower
+from .hybrid import DescrptHybrid
+from .se_a import DescrptSeA
+from .se_r import DescrptSeR
+from .se_ar import DescrptSeAR
+from .se_t import DescrptSeT
+from .se_a_ebd import DescrptSeAEbd
+from .se_a_ef import DescrptSeAEf
+from .se_a_ef import DescrptSeAEfLower
 from .loc_frame import DescrptLocFrame

deepmd/descriptor/hybrid.py

@@ -8,16 +8,16 @@
 from deepmd.env import GLOBAL_NP_FLOAT_PRECISION
 # from deepmd.descriptor import DescrptLocFrame
 # from deepmd.descriptor import DescrptSeA
-# from deepmd.descriptor import DescrptSeAT
+# from deepmd.descriptor import DescrptSeT
 # from deepmd.descriptor import DescrptSeAEbd
 # from deepmd.descriptor import DescrptSeAEf
 # from deepmd.descriptor import DescrptSeR
-from .se_a      import DescrptSeA
-from .se_r      import DescrptSeR
-from .se_ar     import DescrptSeAR
-from .se_a_t    import DescrptSeAT
-from .se_a_ebd  import DescrptSeAEbd
-from .se_a_ef   import DescrptSeAEf
+from .se_a import DescrptSeA
+from .se_r import DescrptSeR
+from .se_ar import DescrptSeAR
+from .se_t import DescrptSeT
+from .se_a_ebd import DescrptSeAEbd
+from .se_a_ef import DescrptSeAEf
 from .loc_frame import DescrptLocFrame
 
 class DescrptHybrid ():

deepmd/descriptor/se_a_t.py → deepmd/descriptor/se_t.py

@@ -10,7 +10,7 @@
 from deepmd.env import default_tf_session_config
 from deepmd.utils.network import embedding_net
 
-class DescrptSeAT ():
+class DescrptSeT ():
     @docstring_parameter(list_to_doc(ACTIVATION_FN_DICT.keys()), list_to_doc(PRECISION_DICT.keys()))
     def __init__ (self, 
                   rcut: float,
@@ -95,7 +95,7 @@ def __init__ (self,
             self.place_holders['natoms_vec'] = tf.placeholder(tf.int32, [self.ntypes+2], name=name_pfx+'t_natoms')
             self.place_holders['default_mesh'] = tf.placeholder(tf.int32, [None], name=name_pfx+'t_mesh')
             self.stat_descrpt, descrpt_deriv, rij, nlist \
-                = op_module.descrpt_se_a(self.place_holders['coord'],
+                = op_module.prod_env_mat_a(self.place_holders['coord'],
                                          self.place_holders['type'],
                                          self.place_holders['natoms_vec'],
                                          self.place_holders['box'],
@@ -282,7 +282,7 @@ def build (self,
         atype = tf.reshape (atype_, [-1, natoms[1]])
 
         self.descrpt, self.descrpt_deriv, self.rij, self.nlist \
-            = op_module.descrpt_se_a (coord,
+            = op_module.prod_env_mat_a (coord,
                                        atype,
                                        natoms,
                                        box,

deepmd/entrypoints/train.py

@@ -15,7 +15,7 @@
 from deepmd.train.run_options import BUILD, CITATION, WELCOME, RunOptions
 from deepmd.train.trainer import DPTrainer
 from deepmd.utils.argcheck import normalize
-from deepmd.utils.compat import convert_input_v0_v1
+from deepmd.utils.compat import updata_deepmd_input
 from deepmd.utils.data_system import DeepmdDataSystem
 
 if TYPE_CHECKING:
@@ -168,8 +168,7 @@ def train(
     # load json database
     jdata = j_loader(INPUT)
 
-    if "model" not in jdata.keys():
-        jdata = convert_input_v0_v1(jdata, warning=True, dump="input_v1_compat.json")
+    jdata = updata_deepmd_input(jdata, warning=True, dump="input_v2_compat.json")
 
     jdata = normalize(jdata)
     with open(output, "w") as fp:

deepmd/train/trainer.py

@@ -11,7 +11,7 @@
 from deepmd.fit import EnerFitting, WFCFitting, PolarFittingLocFrame, PolarFittingSeA, GlobalPolarFittingSeA, DipoleFittingSeA
 from deepmd.descriptor import DescrptLocFrame
 from deepmd.descriptor import DescrptSeA
-from deepmd.descriptor import DescrptSeAT
+from deepmd.descriptor import DescrptSeT
 from deepmd.descriptor import DescrptSeAEbd
 from deepmd.descriptor import DescrptSeAEf
 from deepmd.descriptor import DescrptSeR
@@ -55,16 +55,16 @@ def _generate_descrpt_from_param_dict(descrpt_param):
         descrpt_param.pop(kk, None)
     if descrpt_type == 'loc_frame':
         descrpt = DescrptLocFrame(**descrpt_param)
-    elif descrpt_type == 'se_a' :            
+    elif descrpt_type == 'se_e2_a' or descrpt_type == 'se_a' :
         descrpt = DescrptSeA(**descrpt_param)
-    elif descrpt_type == 'se_a_3be' or descrpt_type == 'se_at' :
-        descrpt = DescrptSeAT(**descrpt_param)
+    elif descrpt_type == 'se_e2_r' or descrpt_type == 'se_r' :
+        descrpt = DescrptSeR(**descrpt_param)
+    elif descrpt_type == 'se_e3' or descrpt_type == 'se_at' or descrpt_type == 'se_a_3be' :
+        descrpt = DescrptSeT(**descrpt_param)
     elif descrpt_type == 'se_a_tpe' or descrpt_type == 'se_a_ebd' :
         descrpt = DescrptSeAEbd(**descrpt_param)
     elif descrpt_type == 'se_a_ef' :
         descrpt = DescrptSeAEf(**descrpt_param)
-    elif descrpt_type == 'se_r' :
-        descrpt = DescrptSeR(**descrpt_param)
     elif descrpt_type == 'se_ar' :
         descrpt = DescrptSeAR(descrpt_param)
     else :
@@ -568,7 +568,7 @@ def valid_on_the_fly(self,
     @staticmethod
     def print_header(fp, train_results, valid_results):
         print_str = ''
-        print_str += "# %5s" % 'batch'
+        print_str += "# %5s" % 'step'
         if valid_results is not None:
             prop_fmt =  '   %11s %11s'
             for k in train_results.keys():

deepmd/utils/argcheck.py

@@ -71,7 +71,7 @@ def descrpt_se_a_args():
     ]
 
 
-def descrpt_se_a_3be_args():
+def descrpt_se_t_args():
     doc_sel = 'A list of integers. The length of the list should be the same as the number of atom types in the system. `sel[i]` gives the selected number of type-i neighbors. `sel[i]` is recommended to be larger than the maximally possible number of type-i neighbors in the cut-off radius.'
     doc_rcut = 'The cut-off radius.'
     doc_rcut_smth = 'Where to start smoothing. For example the 1/r term is smoothed from `rcut` to `rcut_smth`'
@@ -162,24 +162,24 @@ def descrpt_hybrid_args():
 
 def descrpt_variant_type_args():
     link_lf = make_link('loc_frame', 'model/descriptor[loc_frame]')
-    link_se_a = make_link('se_a', 'model/descriptor[se_a]')
-    link_se_r = make_link('se_r', 'model/descriptor[se_r]')
-    link_se_a_3be = make_link('se_a_3be', 'model/descriptor[se_a_3be]')
+    link_se_e2_a = make_link('se_e2_a', 'model/descriptor[se_e2_a]')
+    link_se_e2_r = make_link('se_e2_r', 'model/descriptor[se_e2_r]')
+    link_se_e3 = make_link('se_e3', 'model/descriptor[se_e3]')
     link_se_a_tpe = make_link('se_a_tpe', 'model/descriptor[se_a_tpe]')
     link_hybrid = make_link('hybrid', 'model/descriptor[hybrid]')
     doc_descrpt_type = f'The type of the descritpor. See explanation below. \n\n\
 - `loc_frame`: Defines a local frame at each atom, and the compute the descriptor as local coordinates under this frame.\n\n\
-- `se_a`: Used by the smooth edition of Deep Potential. The full relative coordinates are used to construct the descriptor.\n\n\
-- `se_r`: Used by the smooth edition of Deep Potential. Only the distance between atoms is used to construct the descriptor.\n\n\
-- `se_a_3be`: Used by the smooth edition of Deep Potential. The full relative coordinates are used to construct the descriptor. Three-body embedding will be used by this descriptor.\n\n\
+- `se_e2_a`: Used by the smooth edition of Deep Potential. The full relative coordinates are used to construct the descriptor.\n\n\
+- `se_e2_r`: Used by the smooth edition of Deep Potential. Only the distance between atoms is used to construct the descriptor.\n\n\
+- `se_e3`: Used by the smooth edition of Deep Potential. The full relative coordinates are used to construct the descriptor. Three-body embedding will be used by this descriptor.\n\n\
 - `se_a_tpe`: Used by the smooth edition of Deep Potential. The full relative coordinates are used to construct the descriptor. Type embedding will be used by this descriptor.\n\n\
 - `hybrid`: Concatenate of a list of descriptors as a new descriptor.'
 
     return Variant("type", [
         Argument("loc_frame", dict, descrpt_local_frame_args()),
-        Argument("se_a", dict, descrpt_se_a_args()),
-        Argument("se_r", dict, descrpt_se_r_args()),
-        Argument("se_a_3be", dict, descrpt_se_a_3be_args(), alias = ['se_at']),
+        Argument("se_e2_a", dict, descrpt_se_a_args(), alias = ['se_a']),
+        Argument("se_e2_r", dict, descrpt_se_r_args(), alias = ['se_r']),
+        Argument("se_e3", dict, descrpt_se_t_args(), alias = ['se_at', 'se_a_3be', 'se_t']),
         Argument("se_a_tpe", dict, descrpt_se_a_tpe_args(), alias = ['se_a_ebd']),
         Argument("hybrid", dict, descrpt_hybrid_args()),
     ], doc = doc_descrpt_type)
@@ -553,7 +553,21 @@ def gen_doc(*, make_anchor=True, make_link=True, **kwargs):
     return "\n\n".join(ptr)
 
 
+def normalize_hybrid_list(hy_list):
+    new_list = []
+    base = Argument("base", dict, [], [descrpt_variant_type_args()], doc = "")
+    for ii in range(len(hy_list)):
+        data = base.normalize_value(hy_list[ii], trim_pattern="_*")
+        base.check_value(data, strict=True)
+        new_list.append(data)
+    return new_list
+
+
 def normalize(data):
+    if "hybrid" == data["model"]["descriptor"]["type"]:
+        data["model"]["descriptor"]["list"] \
+            = normalize_hybrid_list(data["model"]["descriptor"]["list"])
+
     ma = model_args()
     lra = learning_rate_args()
     la = loss_args()