Make rust Tensor archetype eager serialized (#8801)

### Related

* sister PR to..
	* #8789
	* #8785
	* #8793
* missed piece of #7245

### What

Ports the Tensor archetype in rust to the new eager serialized
interface.
Unfortunately this meant I had to remove some direct access methods of
the underlying tensor data. Curiously, this didn't affect any of our
test/snippet/example code.
While doing so I also fixed some wording issues in the (very similar)
C++ implementation of `with_dim_names`

Cargo.lock

@@ -6562,6 +6562,7 @@ dependencies = [
  "rayon",
  "re_build_tools",
  "re_byte_size",
+ "re_error",
  "re_format",
  "re_log",
  "re_log_types",

crates/store/re_types/Cargo.toml

@@ -53,9 +53,10 @@ testing = []
 [dependencies]
 # Rerun
 re_byte_size.workspace = true
+re_error.workspace = true
 re_format.workspace = true
-re_log.workspace = true
 re_log_types.workspace = true
+re_log.workspace = true
 re_tracing.workspace = true
 re_types_core.workspace = true
 re_video = { workspace = true, optional = true }

crates/store/re_types/definitions/rerun/archetypes/tensor.fbs

@@ -13,7 +13,7 @@ namespace rerun.archetypes;
 ///
 /// \example archetypes/tensor_simple title="Simple tensor" image="https://static.rerun.io/tensor_simple/baacb07712f7b706e3c80e696f70616c6c20b367/1200w.png"
 table Tensor (
-  // TODO(#7245): "attr.rust.archetype_eager",
+  "attr.rust.archetype_eager",
   "attr.rust.derive": "PartialEq",
   "attr.docs.category": "Image & tensor",
   "attr.docs.view_types": "TensorView, BarChartView: for 1D tensors"

crates/store/re_types/src/archetypes/tensor_ext.rs

@@ -1,25 +1,19 @@
-use crate::datatypes::TensorData;
+use crate::{
+    components::{self},
+    datatypes::TensorData,
+};
 
-use re_types_core::ArrowString;
+use re_types_core::{try_serialize_field, ArrowString, Loggable};
 
 use super::Tensor;
 
 impl Tensor {
-    /// Accessor to the underlying [`TensorData`].
-    pub fn data(&self) -> &TensorData {
-        &self.data.0
-    }
-
     /// Try to construct a [`Tensor`] from anything that can be converted into [`TensorData`]
     ///
     /// This is useful for constructing a tensor from an ndarray.
     pub fn try_from<T: TryInto<TensorData>>(data: T) -> Result<Self, T::Error> {
         let data: TensorData = data.try_into()?;
-
-        Ok(Self {
-            data: data.into(),
-            value_range: None,
-        })
+        Ok(Self::new(data))
     }
 
     /// Update the `names` of the contained [`TensorData`] dimensions.
@@ -32,7 +26,35 @@ impl Tensor {
         mut self,
         names: impl IntoIterator<Item = impl Into<ArrowString>>,
     ) -> Self {
-        self.data.0 = self.data.0.with_dim_names(names);
+        if let Some(data) = self.data.take() {
+            match components::TensorData::from_arrow(&data.array) {
+                Ok(tensor_data) => {
+                    if tensor_data.len() > 1 {
+                        re_log::warn!(
+                            "Can't set dimension names on a tensor archetype with multiple tensor data instances."
+                        );
+                        return self;
+                    }
+                    let Some(tensor_data) = tensor_data.into_iter().next() else {
+                        re_log::warn!(
+                            "Can't set dimension names on a tensor archetype without any tensor data instances."
+                        );
+                        return self;
+                    };
+
+                    self.data = try_serialize_field::<components::TensorData>(
+                        Self::descriptor_data(),
+                        [components::TensorData(tensor_data.0.with_dim_names(names))],
+                    );
+                }
+                Err(err) => re_log::warn!(
+                    "Failed to read arrow tensor data: {}",
+                    re_error::format_ref(&err)
+                ),
+            }
+        } else {
+            re_log::warn!("Can't set names on a tensor that doesn't have any data");
+        }
         self
     }
 }
@@ -45,10 +67,7 @@ impl Tensor {
     pub fn from_image(
         image: impl Into<image::DynamicImage>,
     ) -> Result<Self, crate::tensor_data::TensorImageLoadError> {
-        TensorData::from_image(image).map(|data| Self {
-            data: data.into(),
-            value_range: None,
-        })
+        TensorData::from_image(image).map(Self::new)
     }
 
     /// Construct a tensor from [`image::DynamicImage`].
@@ -57,62 +76,6 @@ impl Tensor {
     pub fn from_dynamic_image(
         image: image::DynamicImage,
     ) -> Result<Self, crate::tensor_data::TensorImageLoadError> {
-        TensorData::from_dynamic_image(image).map(|data| Self {
-            data: data.into(),
-            value_range: None,
-        })
-    }
-}
-
-impl AsRef<TensorData> for Tensor {
-    #[inline(always)]
-    fn as_ref(&self) -> &TensorData {
-        &self.data
-    }
-}
-
-impl std::ops::Deref for Tensor {
-    type Target = TensorData;
-
-    #[inline(always)]
-    fn deref(&self) -> &TensorData {
-        &self.data
+        TensorData::from_dynamic_image(image).map(Self::new)
     }
 }
-
-impl std::borrow::Borrow<TensorData> for Tensor {
-    #[inline(always)]
-    fn borrow(&self) -> &TensorData {
-        &self.data
-    }
-}
-
-// ----------------------------------------------------------------------------
-// Make it possible to create an ArrayView directly from a Tensor.
-
-macro_rules! forward_array_views {
-    ($type:ty, $alias:ty) => {
-        impl<'a> TryFrom<&'a $alias> for ::ndarray::ArrayViewD<'a, $type> {
-            type Error = crate::tensor_data::TensorCastError;
-
-            #[inline]
-            fn try_from(value: &'a $alias) -> Result<Self, Self::Error> {
-                value.data().try_into()
-            }
-        }
-    };
-}
-
-forward_array_views!(u8, Tensor);
-forward_array_views!(u16, Tensor);
-forward_array_views!(u32, Tensor);
-forward_array_views!(u64, Tensor);
-
-forward_array_views!(i8, Tensor);
-forward_array_views!(i16, Tensor);
-forward_array_views!(i32, Tensor);
-forward_array_views!(i64, Tensor);
-
-forward_array_views!(half::f16, Tensor);
-forward_array_views!(f32, Tensor);
-forward_array_views!(f64, Tensor);