Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(eval = FALSE)
## ----eval=FALSE---------------------------------------------------------------
# library(onnx)
# library(reticulate)
# np <- import("numpy", convert = FALSE)
# backend <- import("onnx_tf.backend")
## ----eval=FALSE---------------------------------------------------------------
# load_npz_samples <- function(npz_path) {
# sample <- np$load(normalizePath(npz_path), encoding = 'bytes')
# list(
# inputs = sample$items()[[0]][[1]][[0]],
# outputs = sample$items()[[1]][[1]]
# )
# }
## ----eval=FALSE---------------------------------------------------------------
# # Specify paths to ONNX model and testing samples
# onnx_model_dir <- "~/Downloads/resnet50"
# model_pb_path <- file.path(onnx_model_dir, "model.onnx")
# npz_path <- file.path(onnx_model_dir, "test_data_0.npz")
#
# # Load ONNX model
# model <- load_from_file(model_pb_path)
#
# # Load testing sample from numpy serialized archive
# samples <- load_npz_samples(npz_path)
# inputs <- samples$inputs
# expected_outputs <- samples$outputs
#
# # Run the model with an onnx backend
# actual_outputs <- backend$run_model(model, inputs)
## ----eval=FALSE---------------------------------------------------------------
# np$testing$assert_almost_equal(expected_outputs, actual_outputs, decimal = 6)
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