Resolve tiled slice dimensionality constraint and migrate dsperse (#430)

Author: HudsonGraeme

Cargo.lock

@@ -50,7 +50,7 @@ futures-util = "0.3"
 shellexpand = "3.1.2"
 openssl = { version = "0.10", features = ["vendored"] }
 flate2 = "1"
-dsperse = { git = "https://github.com/inference-labs-inc/dsperse", rev = "8a0c9ddfc8ad7623451549dea784f5a2339a35d3" }
+dsperse = { git = "https://github.com/inference-labs-inc/dsperse", rev = "176ed08ee9552ac23f4a6470d1e7b53b67305b08" }
 ndarray = { version = "0.17", features = ["serde"] }
 zip = { version = "2", default-features = false, features = ["deflate"] }
 bittensor-drand = { git = "https://github.com/inference-labs-inc/bittensor-drand.git", rev = "e55ed98", default-features = false }

Cargo.toml

@@ -322,17 +322,10 @@ impl ValidatorLoop {
         input_tensor: ndarray::ArrayD<f64>,
         run_source: RunSource,
     ) -> Option<usize> {
-        let input_4d = match input_tensor.into_dimensionality::<ndarray::Ix4>() {
-            Ok(arr) => arr,
-            Err(e) => {
-                warn!(run_uid = %run_uid, slice = %slice_id, error = %e, "tiled slice requires 4D input");
-                return None;
-            }
-        };
-        let tiles = match dsperse::pipeline::split_into_tiles(&input_4d, tiling) {
+        let tiles = match dsperse::pipeline::split_for_tiling(&input_tensor, tiling) {
             Ok(t) => t,
             Err(e) => {
-                warn!(run_uid = %run_uid, slice = %slice_id, error = %e, "split_into_tiles failed");
+                warn!(run_uid = %run_uid, slice = %slice_id, error = %e, "split_for_tiling failed");
                 return None;
             }
         };