add flops api unit test (#29228) (#29278)

python/paddle/__init__.py

@@ -273,6 +273,7 @@ from . import onnx
 from .hapi import Model
 from .hapi import callbacks
 from .hapi import summary
+from .hapi import flops
 import paddle.text
 import paddle.vision
 

python/paddle/hapi/__init__.py

@@ -19,7 +19,9 @@ from . import model_summary
 from . import model
 from .model import *
 from .model_summary import summary
+from .dynamic_flops import flops
 
 logger.setup_logger()
 
 __all__ = ['callbacks'] + model.__all__ + ['summary']
+__all__ = model.__all__ + ['flops']

python/paddle/hapi/dynamic_flops.py

@@ -16,7 +16,7 @@ import paddle
 import warnings
 import paddle.nn as nn
 import numpy as np
-from .static_flops import static_flops, _verify_dependent_package
+from .static_flops import static_flops
 
 __all__ = ['flops']
 
@@ -264,7 +264,13 @@ def dynamic_flops(model, inputs, custom_ops=None, print_detail=False):
         model.train()
     for handler in handler_collection:
         handler.remove()
-    _verify_dependent_package()
+
+    try:
+        from prettytable import PrettyTable
+    except ImportError:
+        raise ImportError(
+            "paddle.flops() requires package `prettytable`, place install it firstly using `pip install prettytable`. "
+        )
     table = PrettyTable(
         ["Layer Name", "Input Shape", "Output Shape", "Params", "Flops"])
 

python/paddle/hapi/static_flops.py

@@ -166,22 +166,15 @@ def count_element_op(op):
     return total_ops
 
 
-def _verify_dependent_package():
-    """
-    Verify whether `prettytable` is installed.
-    """
+def _graph_flops(graph, detail=False):
+    assert isinstance(graph, GraphWrapper)
+    flops = 0
     try:
         from prettytable import PrettyTable
     except ImportError:
         raise ImportError(
             "paddle.flops() requires package `prettytable`, place install it firstly using `pip install prettytable`. "
         )
-
-
-def _graph_flops(graph, detail=False):
-    assert isinstance(graph, GraphWrapper)
-    flops = 0
-    _verify_dependent_package()
     table = PrettyTable(["OP Type", 'Param name', "Flops"])
     for op in graph.ops():
         param_name = ''

python/paddle/tests/test_model.py

@@ -33,6 +33,8 @@ from paddle.nn.layer.loss import CrossEntropyLoss
 from paddle.metric import Accuracy
 from paddle.vision.datasets import MNIST
 from paddle.vision.models import LeNet
+import paddle.vision.models as models
+import paddle.fluid.dygraph.jit as jit
 from paddle.io import DistributedBatchSampler, Dataset
 from paddle.hapi.model import prepare_distributed_context
 from paddle.fluid.dygraph.jit import declarative
@@ -564,6 +566,24 @@ class TestModelFunction(unittest.TestCase):
         nlp_net = paddle.nn.GRU(input_size=2, hidden_size=3, num_layers=3)
         paddle.summary(nlp_net, (1, 1, 2))
 
+    def test_static_flops(self):
+        paddle.disable_static()
+        net = models.__dict__['mobilenet_v2'](pretrained=False)
+        inputs = paddle.randn([1, 3, 224, 224])
+        static_program = jit._trace(net, inputs=[inputs])[1]
+        paddle.flops(static_program, [1, 3, 224, 224], print_detail=True)
+
+    def test_dynamic_flops(self):
+        net = models.__dict__['mobilenet_v2'](pretrained=False)
+
+        def customize_dropout(m, x, y):
+            m.total_ops += 0
+
+        paddle.flops(
+            net, [1, 3, 224, 224],
+            custom_ops={paddle.nn.Dropout: customize_dropout},
+            print_detail=True)
+
     def test_export_deploy_model(self):
         self.set_seed()
         np.random.seed(201)