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