Convert remaining yscv-onnx std HashMaps to FxHashMap

The last std::collections::HashMap holdouts: the public `ShapeMap` type
alias and `infer_shapes_from_tensors`' input map, the graph_cost
diagnostic map (usize-keyed — Fx is a clean win there), and the shape/
optimizer test fixtures. Move them all to FxHashMap so the workspace has
zero std HashMap. Tests use FxHashMap::from_iter (no inherent `from`).

Author: enthropy7

crates/yscv-onnx/src/optimizer/graph_cost.rs

@@ -52,7 +52,7 @@ pub fn graph_cost(model: &OnnxModel, shapes: &ShapeInference) -> GraphCost {
     let mut estimated_element_ops = 0u64;
     let mut estimated_bytes_read = 0u64;
     let mut estimated_bytes_written = 0u64;
-    let diagnostic_by_index: std::collections::HashMap<usize, String> = shapes
+    let diagnostic_by_index: rustc_hash::FxHashMap<usize, String> = shapes
         .diagnostics
         .iter()
         .map(|d| (d.node_index, d.error.to_string()))

crates/yscv-onnx/src/shape_infer.rs

@@ -1,4 +1,4 @@
-use std::collections::HashMap;
+use rustc_hash::FxHashMap;
 
 use thiserror::Error;
 use yscv_tensor::Tensor;
@@ -62,7 +62,7 @@ impl TensorShape {
     }
 }
 
-pub type ShapeMap = HashMap<String, TensorShape>;
+pub type ShapeMap = FxHashMap<String, TensorShape>;
 
 #[derive(Debug, Clone, PartialEq, Eq)]
 pub struct ShapeDiagnostic {
@@ -157,7 +157,7 @@ pub fn infer_shapes(model: &OnnxModel, input_shapes: &ShapeMap) -> ShapeInferenc
 
 pub fn infer_shapes_from_tensors(
     model: &OnnxModel,
-    inputs: &HashMap<String, Tensor>,
+    inputs: &FxHashMap<String, Tensor>,
 ) -> ShapeInference {
     let input_shapes: ShapeMap = inputs
         .iter()

crates/yscv-onnx/src/tests/optimizer.rs

@@ -173,7 +173,7 @@ fn graph_cost_report_is_deterministic_and_sorted_by_stable_key() {
     let model = load_onnx_model(&bytes).unwrap();
     let shapes = infer_shapes(
         &model,
-        &std::collections::HashMap::from([
+        &rustc_hash::FxHashMap::from_iter([
             ("mid_a".to_string(), TensorShape::known(vec![1, 4])),
             ("mid_b".to_string(), TensorShape::known(vec![1, 4])),
         ]),
@@ -229,7 +229,7 @@ fn graph_cost_report_shows_lighter_graph_after_optimization() {
     let bytes = build_minimal_onnx_model(nodes, vec![w], vec!["x"], vec!["y"]);
     let mut model = load_onnx_model(&bytes).unwrap();
     let input_shapes =
-        std::collections::HashMap::from([("x".to_string(), TensorShape::known(vec![1, 3, 8, 8]))]);
+        rustc_hash::FxHashMap::from_iter([("x".to_string(), TensorShape::known(vec![1, 3, 8, 8]))]);
 
     let before_shapes = infer_shapes(&model, &input_shapes);
     let before = graph_cost(&model, &before_shapes);

crates/yscv-onnx/src/tests/shape_infer.rs

@@ -1,4 +1,4 @@
-use std::collections::HashMap;
+use rustc_hash::FxHashMap;
 
 use yscv_tensor::Tensor;
 
@@ -40,7 +40,8 @@ fn infers_conv_shape_and_cost() {
         vec!["y"],
     ))
     .unwrap();
-    let input_shapes = HashMap::from([("x".to_string(), TensorShape::known(vec![1, 3, 32, 32]))]);
+    let input_shapes =
+        FxHashMap::from_iter([("x".to_string(), TensorShape::known(vec![1, 3, 32, 32]))]);
 
     let inferred = infer_shapes(&model, &input_shapes);
     assert!(
@@ -84,7 +85,8 @@ fn infers_reshape_and_matmul_shapes() {
         vec!["y"],
     ))
     .unwrap();
-    let input_shapes = HashMap::from([("x".to_string(), TensorShape::known(vec![1, 3, 4, 4]))]);
+    let input_shapes =
+        FxHashMap::from_iter([("x".to_string(), TensorShape::known(vec![1, 3, 4, 4]))]);
 
     let inferred = infer_shapes(&model, &input_shapes);
     assert!(
@@ -116,7 +118,8 @@ fn reports_unknowns_without_guessing() {
         vec!["y"],
     ))
     .unwrap();
-    let input_shapes = HashMap::from([("x".to_string(), TensorShape::known(vec![1, 3, 8, 8]))]);
+    let input_shapes =
+        FxHashMap::from_iter([("x".to_string(), TensorShape::known(vec![1, 3, 8, 8]))]);
 
     let inferred = infer_shapes(&model, &input_shapes);
     assert_eq!(inferred.diagnostics.len(), 1);
@@ -144,7 +147,7 @@ fn infers_shapes_from_initializer_inputs() {
     ))
     .unwrap();
 
-    let inferred = infer_shapes(&model, &HashMap::new());
+    let inferred = infer_shapes(&model, &FxHashMap::default());
     assert_eq!(inferred.shapes["y"].as_known_dims(), Some(vec![2]));
 }
 
@@ -167,7 +170,8 @@ fn global_average_pool_cost_reads_spatial_from_inferred_shape() {
         vec!["y"],
     ))
     .unwrap();
-    let input_shapes = HashMap::from([("x".to_string(), TensorShape::known(vec![1, 8, 4, 4]))]);
+    let input_shapes =
+        FxHashMap::from_iter([("x".to_string(), TensorShape::known(vec![1, 8, 4, 4]))]);
 
     let inferred = infer_shapes(&model, &input_shapes);
     assert!(