[WIP]Add test module to Gluon-Face

gluonfr/model_zoo/attention_net.py

@@ -327,7 +327,7 @@ def get_attention_net(classes, num_layers, **kwargs):
     ptr, modules = attention_net_spec[num_layers]
     assert len(ptr) == len(modules) == 3
     p, t, r = ptr
-    net = AttentionNet(classes, modules, p, t, r, **kwargs)
+    net = AttentionNetFace(classes, modules, p, t, r, **kwargs)
     return net
 
 

tests/README.md

@@ -0,0 +1,4 @@
+# This is Gluon-Face test module.
+
+We use pytest as our test runner
+and will use Jenkins+Github as CI.

tests/unittests/common.py

@@ -0,0 +1,44 @@
+# -*- coding: utf-8 -*-
+# @Author  : PistonYang(pistonyang@gmail.com)
+
+
+import mxnet as mx
+import functools
+
+
+def try_gpu(gpu_id=0):
+    """Try execute on gpu, if not fallback to cpu"""
+
+    def test_helper(orig_test):
+        @functools.wraps(orig_test)
+        def test_wapper(*args, **kwargs):
+            try:
+                a = mx.nd.zeros((1,), ctx=mx.gpu(gpu_id))
+                ctx = mx.gpu(gpu_id)
+            except Exception:
+                ctx = mx.cpu()
+            with ctx:
+                orig_test(*args, **kwargs)
+
+        return test_wapper
+
+    return test_helper
+
+
+def try_cpu(cpu_id=0):
+    """Try execute on gpu, if not fallback to cpu"""
+
+    def test_helper(orig_test):
+        @functools.wraps(orig_test)
+        def test_wapper(*args, **kwargs):
+            try:
+                a = mx.nd.zeros((1,), ctx=mx.cpu(cpu_id))
+                ctx = mx.gpu(cpu_id)
+            except Exception:
+                ctx = mx.cpu(0)
+            with ctx:
+                orig_test(*args, **kwargs)
+
+        return test_wapper
+
+    return test_helper

tests/unittests/test_basic_block.py

@@ -0,0 +1,38 @@
+# -*- coding: utf-8 -*-
+# @Author  : PistonYang(pistonyang@gmail.com)
+
+import pytest
+import mxnet as mx
+from mxnet import nd
+from mxnet.gluon import nn
+from gluonfr.nn.basic_blocks import FrBase
+from tests.unittests.common import try_gpu
+
+
+class Model(FrBase):
+    def __init__(self, embedding_size=1, weight_norm=False, feature_norm=False,
+                 need_cls_layer=True):
+        super(Model, self).__init__(1, embedding_size, weight_norm, feature_norm, need_cls_layer)
+        self.features = nn.HybridSequential()
+        self.features.add(
+            nn.Conv2D(16, 3, 1, 1, use_bias=False),
+            nn.BatchNorm(),
+            nn.Dense(embedding_size, use_bias=False),
+            nn.BatchNorm(center=False, scale=False),
+        )
+
+
+@pytest.fixture(params=[[16, False, False, False],
+                        [16, True, True, False],
+                        [16, True, True, True]])
+def get_model(request):
+    return Model(*request.param)
+
+
+@try_gpu(0)
+def test_model(get_model):
+    ctx = mx.context.current_context()
+    x = nd.random.normal(shape=(2, 3, 112, 112), ctx=ctx)
+    model = get_model
+    model.initialize(ctx=ctx)
+    model(x)

tests/unittests/test_data_dataloader.py

@@ -0,0 +1,5 @@
+# -*- coding: utf-8 -*-
+# @Author  : PistonYang(pistonyang@gmail.com)
+
+"""No additional Dataloader to test"""
+pass

tests/unittests/test_data_datasets.py

@@ -0,0 +1,43 @@
+# -*- coding: utf-8 -*-
+# @Author  : PistonYang(pistonyang@gmail.com)
+
+import pytest
+import numpy as np
+from gluonfr.data.dataset import FRValDataset, FRTrainRecordDataset
+
+train_sets = ['vgg', 'webface', 'emore']
+val_sets = ['agedb_30', 'calfw', 'cfp_ff', 'cfp_fp', 'cplfw', 'lfw']
+
+
+def parse_sets(datasets):
+    return [[dataset] for dataset in datasets]
+
+
+@pytest.fixture(params=parse_sets(train_sets))
+def get_train_datasets(request):
+    dt = FRTrainRecordDataset(*request.param)
+    return dt
+
+
+@pytest.fixture(params=parse_sets(val_sets))
+def get_val_datasets(request):
+    dt = FRValDataset(*request.param)
+    return dt
+
+
+def test_train_datasets(get_train_datasets):
+    dt = get_train_datasets
+    for _ in range(10):
+        index = np.random.randint(0, len(dt))
+        img, label = dt[index]
+        assert img.shape == (112, 112, 3)
+        assert type(label) is float
+
+
+def test_val_datasets(get_val_datasets):
+    dt = get_val_datasets
+    for _ in range(10):
+        index = np.random.randint(0, len(dt))
+        imgs, label = dt[index]
+        assert imgs[0].shape == imgs[1].shape == (112, 112, 3)
+        assert label in (0, 1)

tests/unittests/test_loss.py

@@ -0,0 +1,4 @@
+# -*- coding: utf-8 -*-
+# @Author  : PistonYang(pistonyang@gmail.com)
+"""loss test please look at our examples."""
+pass

tests/unittests/test_model_zoo.py

@@ -0,0 +1,18 @@
+# -*- coding: utf-8 -*-
+# @Author  : PistonYang(pistonyang@gmail.com)
+
+import mxnet as mx
+from gluonfr.model_zoo.model_zoo import *
+from tests.unittests.common import try_gpu
+
+
+@try_gpu(0)
+def test_model_zoo():
+    ctx = mx.context.current_context()
+    models = get_model_list()
+    data = mx.random.normal(shape=(2, 3, 112, 112), ctx=ctx)
+    for model_name in models:
+        model = get_model(model_name, classes=10, weight_norm=True, feature_norm=True)
+        model.initialize(ctx=ctx)
+        model(data)
+        mx.nd.waitall()