add component usage demo (#537)

add component usage demo

demo/component/audio_demo.py

+import numpy as np
+import wave
+from visualdl import LogWriter
+
+num_samples = 1
+
+
+def read_audio_data(audio_path):
+    CHUNK = 4096
+    f = wave.open(audio_path, "rb")
+    wavdata = []
+    chunk = f.readframes(CHUNK)
+
+    while chunk:
+        data = np.fromstring(chunk, dtype='uint8')
+        wavdata.extend(data)
+        chunk = f.readframes(CHUNK)
+
+    # 8k sample rate, 16bit frame, 1 channel
+    shape = [8000, 2, 1]
+
+    return shape, wavdata
+
+
+def record_audio(vdl_audio_comp):
+    sample_num = 0
+    record_times = num_samples * 3
+    audio_path = "test.wav"
+    for i in range(record_times):
+        if sample_num % num_samples == 0:
+            vdl_audio_comp.start_sampling()
+        idx = vdl_audio_comp.is_sample_taken()
+        if idx != -1:
+            audio_shape, audio_data = read_audio_data(audio_path)
+            vdl_audio_comp.set_sample(idx, audio_shape, audio_data)
+            sample_num += 1
+            if sample_num % num_samples == 0:
+                vdl_audio_comp.finish_sampling()
+                sample_num = 0
+
+
+def main():
+    log_writter = LogWriter("./vdl_log", sync_cycle=10)
+    with log_writter.mode("train") as logger:
+        vdl_audio_comp = logger.audio(tag="test", num_samples=num_samples)
+
+    # after record, use visualdl --logdir vdl_log to load the log info,
+    # and view the data in webpage
+    record_audio(vdl_audio_comp)
+
+
+if __name__ == "__main__":
+    main()

demo/component/embeeding_demo.py

+import numpy as np
+from visualdl import LogWriter
+
+
+def record_embedding(vdl_embedding_comp):
+    hot_vectors = np.random.uniform(1, 2, size=(10, 3))
+    word_dict = {
+        "label1": 1,
+        "label2": 2,
+        "label3": 3,
+    }
+
+    vdl_embedding_comp.add_embeddings_with_word_dict(hot_vectors, word_dict)
+
+
+def main():
+    log_writter = LogWriter("./vdl_log", sync_cycle=10)
+    with log_writter.mode("train") as logger:
+        vdl_embedding_comp = logger.embedding()
+
+    # after record, use visualdl --logdir vdl_log to load the log info,
+    # and view the data in webpage
+    record_embedding(vdl_embedding_comp)
+
+
+if __name__ == "__main__":
+    main()

demo/component/graph_demo.py

+import paddle.fluid as fluid
+
+
+def lenet_5(img):
+    conv1 = fluid.nets.simple_img_conv_pool(
+        input=img,
+        filter_size=5,
+        num_filters=20,
+        pool_size=2,
+        pool_stride=2,
+        act="relu")
+
+    conv1_bn = fluid.layers.batch_norm(input=conv1)
+
+    conv2 = fluid.nets.simple_img_conv_pool(
+        input=conv1_bn,
+        filter_size=5,
+        num_filters=50,
+        pool_size=2,
+        pool_stride=2,
+        act="relu")
+
+    predition = fluid.layers.fc(input=conv2, size=10, act="softmax")
+    return predition
+
+
+def main():
+    image = fluid.layers.data(name="img", shape=[1, 28, 28], dtype="float32")
+    predition = lenet_5(image)
+
+    place = fluid.CPUPlace()
+    exe = fluid.Executor(place=place)
+    exe.run(fluid.default_startup_program())
+    # after record, use visualdl --logdir [LOGDIR] --model_pb paddle_lenet_5_model to load the model,
+    # and view the data in webpage
+    fluid.io.save_inference_model(
+        "./paddle_lenet_5_model",
+        feeded_var_names=[image.name],
+        target_vars=[predition],
+        executor=exe)
+
+
+if __name__ == "__main__":
+    main()

demo/component/histogram_demo.py

+import numpy as np
+from visualdl import LogWriter
+
+
+def record_histogram(vdl_histogram_comp):
+    for i in range(1, 101):
+        f = 1 + 2 * i / 100
+        t = 6 - 2 * i / 100
+        data = np.random.uniform(f, t, size=(500))
+        vdl_histogram_comp.add_record(i, data)
+
+
+def main():
+    log_writter = LogWriter("./vdl_log", sync_cycle=10)
+    with log_writter.mode("train") as logger:
+        vdl_histogram_comp = logger.histogram(tag="test", num_buckets=50)
+
+    # after record, use visualdl --logdir vdl_log to load the log info,
+    # and view the data in webpage
+    record_histogram(vdl_histogram_comp)
+
+
+if __name__ == "__main__":
+    main()

demo/component/image_demo.py

+import numpy as np
+from visualdl import LogWriter
+from PIL import Image
+
+num_samples = 1
+
+
+def random_crop(img):
+    img = Image.open(img)
+    w, h = img.size
+    random_w = np.random.randint(0, w - 100)
+    random_h = np.random.randint(0, h - 100)
+    return img.crop((random_w, random_h, random_w + 100, random_h + 100))
+
+
+def record_image(vdl_image_comp):
+    sample_num = 0
+    record_times = num_samples * 3
+    image_path = "test.jpg"
+    for i in range(record_times):
+        if sample_num % num_samples == 0:
+            vdl_image_comp.start_sampling()
+        idx = vdl_image_comp.is_sample_taken()
+        if idx != -1:
+            image_data = np.array(random_crop(image_path))
+            vdl_image_comp.set_sample(idx, image_data.shape,
+                                      image_data.flatten())
+            sample_num += 1
+            if sample_num % num_samples == 0:
+                vdl_image_comp.finish_sampling()
+                sample_num = 0
+
+
+def main():
+    log_writter = LogWriter("./vdl_log", sync_cycle=10)
+    with log_writter.mode("train") as logger:
+        vdl_image_comp = logger.image(tag="test", num_samples=num_samples)
+
+    # after record, use visualdl --logdir vdl_log to load the log info,
+    # and view the data in webpage
+    record_image(vdl_image_comp)
+
+
+if __name__ == "__main__":
+    main()

demo/component/scalar_demo.py

+from visualdl import LogWriter
+
+
+def record_scalar(vdl_scalar_comp):
+    for i in range(1, 101):
+        vdl_scalar_comp.add_record(i, i**2)
+
+
+def main():
+    log_writter = LogWriter("./vdl_log", sync_cycle=10)
+    with log_writter.mode("train") as logger:
+        vdl_scalar_comp = logger.scalar(tag="test")
+
+    # after record, use visualdl --logdir vdl_log to load the log info,
+    # and view the data in webpage
+    record_scalar(vdl_scalar_comp)
+
+
+if __name__ == "__main__":
+    main()

demo/component/text_demo.py

+from visualdl import LogWriter
+
+
+def record_text(vdl_text_comp):
+    for i in range(1, 6):
+        vdl_text_comp.add_record(i, "this is test text_%d" % i)
+
+
+def main():
+    log_writter = LogWriter("./vdl_log", sync_cycle=10)
+    with log_writter.mode("train") as logger:
+        vdl_text_comp = logger.text(tag="test")
+
+    # after record, use visualdl --logdir vdl_log to load the log info,
+    # and view the data in webpage
+    record_text(vdl_text_comp)
+
+
+if __name__ == "__main__":
+    main()