chore: import upstream snapshot with attribution

r/example/mobilenet.py

@@ -0,0 +1,64 @@
+#!/usr/bin/env python3.8
+
+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import numpy as np
+
+from paddle.base.core import AnalysisConfig, create_paddle_predictor
+
+
+def main():
+    config = set_config()
+    predictor = create_paddle_predictor(config)
+
+    data, result = parse_data()
+
+    input_names = predictor.get_input_names()
+    input_tensor = predictor.get_input_tensor(input_names[0])
+    shape = (1, 3, 300, 300)
+    input_data = data[:-4].astype(np.float32).reshape(shape)
+    input_tensor.copy_from_cpu(input_data)
+
+    predictor.zero_copy_run()
+
+    output_names = predictor.get_output_names()
+    output_tensor = predictor.get_output_tensor(output_names[0])
+    output_data = output_tensor.copy_to_cpu()
+
+
+def set_config():
+    config = AnalysisConfig("")
+    config.set_model("model/__model__", "model/__params__")
+    config.switch_use_feed_fetch_ops(False)
+    config.switch_specify_input_names(True)
+    config.enable_profile()
+
+    return config
+
+
+def parse_data():
+    """parse input and output data"""
+    with open('data/data.txt', 'r') as fr:
+        data = np.array([float(_) for _ in fr.read().split()])
+
+    with open('data/result.txt', 'r') as fr:
+        result = np.array([float(_) for _ in fr.read().split()])
+
+    return (data, result)
+
+
+if __name__ == "__main__":
+    main()

r/example/mobilenet.r

@@ -0,0 +1,45 @@
+#!/usr/bin/env Rscript
+
+library(reticulate) # call Python library
+
+use_python("/opt/python3.8/bin/python")
+
+np <- import("numpy")
+paddle <- import("paddle.base.core")
+
+set_config <- function() {
+    config <- paddle$AnalysisConfig("")
+    config$set_model("data/model/__model__", "data/model/__params__")
+    config$switch_use_feed_fetch_ops(FALSE)
+    config$switch_specify_input_names(TRUE)
+    config$enable_profile()
+
+    return(config)
+}
+
+zero_copy_run_mobilenet <- function() {
+    data <- np$loadtxt("data/data.txt")
+    data <- data[0:(length(data) - 4)]
+    result <- np$loadtxt("data/result.txt")
+    result <- result[0:(length(result) - 4)]
+
+    config <- set_config()
+    predictor <- paddle$create_paddle_predictor(config)
+
+    input_names <- predictor$get_input_names()
+    input_tensor <- predictor$get_input_tensor(input_names[1])
+    input_data <- np_array(data, dtype="float32")$reshape(as.integer(c(1, 3, 300, 300)))
+    input_tensor$copy_from_cpu(input_data)
+
+    predictor$zero_copy_run()
+
+    output_names <- predictor$get_output_names()
+    output_tensor <- predictor$get_output_tensor(output_names[1])
+    output_data <- output_tensor$copy_to_cpu()
+    output_data <- np_array(output_data)$reshape(as.integer(-1))
+    #all.equal(output_data, result)
+}
+
+if (!interactive()) {
+    zero_copy_run_mobilenet()
+}