chore: provide multiple typemap zbl torch

deepmd/pt/model/model/__init__.py

@@ -82,7 +82,7 @@ def get_spin_model(model_params):
 
 def get_zbl_model(model_params):
     model_params = copy.deepcopy(model_params)
-    ntypes = len(model_params["type_map"])
+    ntypes = len(model_params["type_map"]["zbl"])
     # descriptor
     model_params["descriptor"]["ntypes"] = ntypes
     descriptor = BaseDescriptor(**model_params["descriptor"])
@@ -99,14 +99,14 @@ def get_zbl_model(model_params):
         if "ener" in fitting_net["type"]:
             fitting_net["return_energy"] = True
     fitting = BaseFitting(**fitting_net)
-    dp_model = DPAtomicModel(descriptor, fitting, type_map=model_params["type_map"])
+    dp_model = DPAtomicModel(descriptor, fitting, type_map=model_params["type_map"]["dp"])
     # pairtab
     filepath = model_params["use_srtab"]
     pt_model = PairTabAtomicModel(
         filepath,
         model_params["descriptor"]["rcut"],
         model_params["descriptor"]["sel"],
-        type_map=model_params["type_map"],
+        type_map=model_params["type_map"]["pairtab"],
     )
 
     rmin = model_params["sw_rmin"]
@@ -118,7 +118,7 @@ def get_zbl_model(model_params):
         pt_model,
         rmin,
         rmax,
-        type_map=model_params["type_map"],
+        type_map=model_params["type_map"]["zbl"],
         atom_exclude_types=atom_exclude_types,
         pair_exclude_types=pair_exclude_types,
     )

examples/water/zbl/input_torch.json

@@ -0,0 +1,94 @@
+{
+    "_comment1": " model parameters",
+    "model": {
+      "use_srtab": "H2O_tab_potential.txt",
+      "smin_alpha": 0.1,
+      "sw_rmin": 0.8,
+      "sw_rmax": 1.0,
+      "type_map": {
+        "pairtab":["O","H"],
+        "dp": ["O", "H"],
+        "zbl": ["O", "H"]
+      },
+      "descriptor": {
+        "type": "se_e2_a",
+        "sel": [
+          46,
+          92
+        ],
+        "rcut_smth": 0.50,
+        "rcut": 6.00,
+        "neuron": [
+          25,
+          50,
+          100
+        ],
+        "resnet_dt": false,
+        "axis_neuron": 16,
+        "type_one_side": true,
+        "precision": "float64",
+        "seed": 1,
+        "_comment2": " that's all"
+      },
+      "fitting_net": {
+        "neuron": [
+          240,
+          240,
+          240
+        ],
+        "resnet_dt": true,
+        "precision": "float64",
+        "seed": 1,
+        "_comment3": " that's all"
+      },
+      "_comment4": " that's all"
+    },
+
+    "learning_rate": {
+      "type": "exp",
+      "decay_steps": 5000,
+      "start_lr": 0.001,
+      "stop_lr": 3.51e-8,
+      "_comment5": "that's all"
+    },
+
+    "loss": {
+      "type": "ener",
+      "start_pref_e": 0.02,
+      "limit_pref_e": 1,
+      "start_pref_f": 1000,
+      "limit_pref_f": 1,
+      "start_pref_v": 0,
+      "limit_pref_v": 0,
+      "_comment6": " that's all"
+    },
+
+    "training": {
+      "training_data": {
+        "systems": [
+          "../data/data_0/",
+          "../data/data_1/",
+          "../data/data_2/"
+        ],
+        "batch_size": "auto",
+        "_comment7": "that's all"
+      },
+      "validation_data": {
+        "systems": [
+          "../data/data_3"
+        ],
+        "batch_size": 1,
+        "numb_btch": 3,
+        "_comment8": "that's all"
+      },
+      "numb_steps": 1000000,
+      "seed": 10,
+      "disp_file": "lcurve.out",
+      "disp_freq": 100,
+      "save_freq": 1000,
+      "_comment9": "that's all"
+    },
+
+    "_comment10": "that's all"
+  }
+

source/tests/pt/model/water/zbl.json

@@ -5,10 +5,11 @@
     "smin_alpha": 0.1,
     "sw_rmin": 0.8,
     "sw_rmax": 1.0,
-    "type_map": [
-      "O",
-      "H"
-    ],
+    "type_map": {
+      "pairtab":["O","H"],
+      "dp": ["O", "H"],
+      "zbl": ["O", "H"]
+    },
     "descriptor": {
       "type": "se_e2_a",
       "sel": [