From a22661bb5bb57adc3a02093d00a0ef57650eb8d3 Mon Sep 17 00:00:00 2001
From: Mathieu Poumeyrol <kali@zoy.org>
Date: Mon, 28 Aug 2023 14:49:21 +0200
Subject: [PATCH] change parameters names

---
 cli/src/main.rs   | 20 +++++++++++---------
 cli/src/run.rs    |  4 ++--
 cli/src/tensor.rs |  4 ++--
 3 files changed, 15 insertions(+), 13 deletions(-)

diff --git a/cli/src/main.rs b/cli/src/main.rs
index 684ffaa5f1..a8cc6eab82 100644
--- a/cli/src/main.rs
+++ b/cli/src/main.rs
@@ -195,16 +195,17 @@ fn main() -> tract_core::anyhow::Result<()> {
         .long_about("Run the graph")
         .arg(Arg::new("dump").long("dump").help("Show output"))
         .arg(
-            Arg::new("save-outputs")
-                .long("save-outputs")
+            Arg::new("save-outputs-npz")
+                .long("save-outputs-npz")
+                .alias("save-outputs")
                 .takes_value(true)
                 .help("Save the outputs into a npz file"),
         )
         .arg(
-            Arg::new("save-output-tensors")
-                .long("save-output-tensors")
+            Arg::new("save-outputs-nnef")
+                .long("save-outputs-nnef")
                 .takes_value(true)
-                .help("Save the output tensor into a .dat file"),
+                .help("Save the output tensor into a folder of nnef .dat files"),
         )
         .arg(Arg::new("steps").long("steps").help("Show all inputs and outputs"))
         .arg(
@@ -401,14 +402,15 @@ fn run_options(command: clap::Command) -> clap::Command {
     use clap::*;
     command
         .arg(
-            Arg::new("input-from-bundle")
-                .long("input-from-bundle")
+            Arg::new("input-from-npz")
+                .long("input-from-npz")
+                .alias("input-from-bundle")
                 .takes_value(true)
                 .help("Path to an input container (.npz). This sets tensor values."),
         )
         .arg(
-            Arg::new("input-from-tensors").long("input-from-tensors").takes_value(true).help(
-                "Path to a directory containing input tensors (.dat). This sets tensor values.",
+            Arg::new("input-from-nnef").long("input-from-nnef").takes_value(true).help(
+                "Path to a directory containing input tensors in NNEF format (.dat files). This sets tensor values.",
             ),
         )
         .arg(
diff --git a/cli/src/run.rs b/cli/src/run.rs
index dc3ee4cc1c..4dea92bdd8 100644
--- a/cli/src/run.rs
+++ b/cli/src/run.rs
@@ -60,7 +60,7 @@ pub fn handle(
         }
     }
 
-    if let Some(file_path) = sub_matches.value_of("save-output-tensors") {
+    if let Some(file_path) = sub_matches.value_of("save-outputs-nnef") {
         std::fs::create_dir_all(file_path)
             .with_context(|| format!("Creating {file_path} directory"))?;
         for (ix, outputs) in outputs.iter().enumerate() {
@@ -83,7 +83,7 @@ pub fn handle(
         }
     }
 
-    if let Some(file_path) = sub_matches.value_of("save-outputs") {
+    if let Some(file_path) = sub_matches.value_of("save-outputs-npz") {
         let file =
             std::fs::File::create(file_path).with_context(|| format!("Creating {file_path}"))?;
         let mut npz = ndarray_npy::NpzWriter::new_compressed(file);
diff --git a/cli/src/tensor.rs b/cli/src/tensor.rs
index 161307a93b..72dc3d0342 100644
--- a/cli/src/tensor.rs
+++ b/cli/src/tensor.rs
@@ -9,7 +9,7 @@ pub fn run_params_from_subcommand(
 ) -> TractResult<RunParams> {
     let mut tv = params.tensors_values.clone();
 
-    if let Some(bundle) = sub_matches.values_of("input-from-bundle") {
+    if let Some(bundle) = sub_matches.values_of("input-from-npz") {
         for input in bundle {
             for tensor in Parameters::parse_npz(input, true, false)? {
                 tv.add(tensor);
@@ -17,7 +17,7 @@ pub fn run_params_from_subcommand(
         }
     }
 
-    if let Some(dir) = sub_matches.value_of("input-from-tensors") {
+    if let Some(dir) = sub_matches.value_of("input-from-nnef") {
         for tensor in Parameters::parse_nnef_tensors(dir, true, false)? {
             tv.add(tensor);
         }