Add a more detailed introduction for model compression

deepmd/entrypoints/compress.py

@@ -23,7 +23,7 @@ def compress(
     input: str,
     output: str,
     extrapolate: int,
-    stride: float,
+    step: float,
     frequency: str,
     checkpoint_folder: str,
     mpi_log: str,
@@ -34,9 +34,9 @@ def compress(
     """Compress model.
 
     The table is composed of fifth-order polynomial coefficients and is assembled from
-    two sub-tables. The first table takes the stride(parameter) as it's uniform stride,
-    while the second table takes 10 * stride as it's uniform stride. The range of the
-    first table is automatically detected by deepmd-kit, while the second table ranges
+    two sub-tables. The first table takes the step parameter as the domain's uniform step size,
+    while the second table takes 10 * step as it's uniform step size. The range of the
+    first table is automatically detected by the code, while the second table ranges
     from the first table's upper boundary(upper) to the extrapolate(parameter) * upper.
 
     Parameters
@@ -49,8 +49,8 @@ def compress(
         compressed model filename
     extrapolate : int
         scale of model extrapolation
-    stride : float
-        uniform stride of tabulation's first table
+    step : float
+        uniform step size of the tabulation's first table
     frequency : str
         frequency of tabulation overflow check
     checkpoint_folder : str
@@ -71,8 +71,8 @@ def compress(
     jdata["model"]["compress"]["model_file"] = input
     jdata["model"]["compress"]["table_config"] = [
         extrapolate,
-        stride,
-        10 * stride,
+        step,
+        10 * step,
         int(frequency),
     ]
     # be careful here, if one want to refine the model

deepmd/entrypoints/main.py

@@ -242,8 +242,8 @@ def parse_args(args: Optional[List[str]] = None):
     # * compress model *****************************************************************
     # Compress a model, which including tabulating the embedding-net.
     # The table is composed of fifth-order polynomial coefficients and is assembled
-    # from two sub-tables. The first table takes the stride(parameter) as it's uniform
-    # stride, while the second table takes 10 * stride as it\s uniform stride
+    # from two sub-tables. The first table takes the step(parameter) as it's uniform
+    # step, while the second table takes 10 * step as it\s uniform step
     #  The range of the first table is automatically detected by deepmd-kit, while the
     # second table ranges from the first table's upper boundary(upper) to the
     # extrapolate(parameter) * upper.
@@ -263,36 +263,43 @@ def parse_args(args: Optional[List[str]] = None):
         "--input",
         default="frozen_model.pb",
         type=str,
-        help="The original frozen model, which will be compressed by the deepmd-kit",
+        help="The original frozen model, which will be compressed by the code",
     )
     parser_compress.add_argument(
         "-o",
         "--output",
-        default="frozen_model_compress.pb",
+        default="frozen_model_compressed.pb",
         type=str,
         help="The compressed model",
     )
+    parser_compress.add_argument(
+        "-s",
+        "--step",
+        default=0.01,
+        type=float,
+        help="Model compression uses fifth-order polynomials to interpolate the embedding-net. " 
+        "It introduces two tables with different step size to store the parameters of the polynomials. "
+        "The first table covers the range of the training data, while the second table is an extrapolation of the training data. "
+        "The domain of each table is uniformly divided by a given step size. "
+        "And the step(parameter) denotes the step size of the first table and the second table will "
+        "use 10 * step as it's step size to save the memory. "
+        "Usually the value ranges from 0.1 to 0.001. " 
+        "Smaller step means higher accuracy and bigger model size",
+    )
     parser_compress.add_argument(
         "-e",
         "--extrapolate",
         default=5,
         type=int,
-        help="The scale of model extrapolation",
-    )
-    parser_compress.add_argument(
-        "-s",
-        "--stride",
-        default=0.01,
-        type=float,
-        help="The uniform stride of tabulation's first table, the second table will "
-        "use 10 * stride as it's uniform stride",
+        help="The domain range of the first table is automatically detected by the code: [d_low, d_up]. "
+        "While the second table ranges from the first table's upper boundary(d_up) to the extrapolate(parameter) * d_up: [d_up, extrapolate * d_up]",
     )
     parser_compress.add_argument(
         "-f",
         "--frequency",
         default=-1,
         type=int,
-        help="The frequency of tabulation overflow check(If the input environment "
+        help="The frequency of tabulation overflow check(Whether the input environment "
         "matrix overflow the first or second table range). "
         "By default do not check the overflow",
     )

doc/getting-started.md

@@ -244,23 +244,50 @@ positional arguments:
 
 optional arguments:
   -h, --help            show this help message and exit
+  -v {DEBUG,3,INFO,2,WARNING,1,ERROR,0}, --log-level {DEBUG,3,INFO,2,WARNING,1,ERROR,0}
+                        set verbosity level by string or number, 0=ERROR,
+                        1=WARNING, 2=INFO and 3=DEBUG (default: INFO)
+  -l LOG_PATH, --log-path LOG_PATH
+                        set log file to log messages to disk, if not
+                        specified, the logs will only be output to console
+                        (default: None)
+  -m {master,collect,workers}, --mpi-log {master,collect,workers}
+                        Set the manner of logging when running with MPI.
+                        'master' logs only on main process, 'collect'
+                        broadcasts logs from workers to master and 'workers'
+                        means each process will output its own log (default:
+                        master)
   -i INPUT, --input INPUT
                         The original frozen model, which will be compressed by
-                        the deepmd-kit
+                        the code (default: frozen_model.pb)
   -o OUTPUT, --output OUTPUT
-                        The compressed model
+                        The compressed model (default:
+                        frozen_model_compressed.pb)
+  -s STEP, --step STEP  Model compression uses fifth-order polynomials to
+                        interpolate the embedding-net. It introduces two
+                        tables with different step size to store the
+                        parameters of the polynomials. The first table covers
+                        the range of the training data, while the second table
+                        is an extrapolation of the training data. The domain
+                        of each table is uniformly divided by a given step
+                        size. And the step(parameter) denotes the step size of
+                        the first table and the second table will use 10 *
+                        step as it's step size to save the memory. Usually the
+                        value ranges from 0.1 to 0.001. Smaller step means
+                        higher accuracy and bigger model size (default: 0.01)
   -e EXTRAPOLATE, --extrapolate EXTRAPOLATE
-                        The scale of model extrapolation
-  -s STRIDE, --stride STRIDE
-                        The uniform stride of tabulation's first table, the
-                        second table will use 10 * stride as it's uniform
-                        stride
+                        The domain range of the first table is automatically
+                        detected by the code: [d_low, d_up]. While the second
+                        table ranges from the first table's upper
+                        boundary(d_up) to the extrapolate(parameter) * d_up:
+                        [d_up, extrapolate * d_up] (default: 5)
   -f FREQUENCY, --frequency FREQUENCY
-                        The frequency of tabulation overflow check(If the
+                        The frequency of tabulation overflow check(Whether the
                         input environment matrix overflow the first or second
                         table range). By default do not check the overflow
-  -d FOLDER, --folder FOLDER
-                        path to checkpoint folder
+                        (default: -1)
+  -c CHECKPOINT_FOLDER, --checkpoint-folder CHECKPOINT_FOLDER
+                        path to checkpoint folder (default: .)
 ```
 **Parameter explanation**
 

source/tests/test_argument_parser.py

@@ -272,10 +272,10 @@ def test_parser_compress(self):
         ARGS = {
             "INPUT": dict(type=str, value="INFILE"),
             "--output": dict(type=str, value="OUTFILE"),
-            "--extrapolate": dict(type=int, value=10),
-            "--stride": dict(type=float, value=0.1),
-            "--frequency": dict(type=int, value=1),
-            "--checkpoint-folder": dict(type=str, value="FOLDER"),
+            "--extrapolate": dict(type=int, value=5),
+            "--step": dict(type=float, value=0.1),
+            "--frequency": dict(type=int, value=-1),
+            "--checkpoint-folder": dict(type=str, value="."),
         }
 
         self.run_test(command="compress", mapping=ARGS)