[Docs] Document every implemented op the API reference was missing

docs/api/attention.md

@@ -45,6 +45,12 @@ what runs when you call `op(...)`.
       heading_level: 3
       members: ["__init__", "forward"]
 
+::: tileops.ops.attention.gqa.GroupedQueryAttentionDenseFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
 ::: tileops.ops.attention.gqa.GroupedQueryAttentionPrefillFwdOp
     options:
       show_root_heading: true
@@ -122,3 +128,11 @@ what runs when you call `op(...)`.
       show_root_heading: true
       heading_level: 3
       members: ["__init__", "forward"]
+
+## Attention indexing
+
+::: tileops.ops.fp8_lightning_indexer.FP8LightningIndexerFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]

docs/api/convolution.md

@@ -0,0 +1,26 @@
+# Convolution Operators
+
+Every op on this page is used the same way: construct it once, then call it. The
+constructor takes what the kernel is compiled with; the call takes the tensors.
+Both are documented under each op — `__init__` and `forward`, where `forward` is
+what runs when you call `op(...)`.
+
+## Forward convolution
+
+::: tileops.ops.convolution.Conv1dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.convolution.Conv2dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.convolution.Conv3dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]

docs/api/dropout.md

@@ -0,0 +1,14 @@
+# Dropout Operators
+
+Every op on this page is used the same way: construct it once, then call it. The
+constructor takes what the kernel is compiled with; the call takes the tensors.
+Both are documented under each op — `__init__` and `forward`, where `forward` is
+what runs when you call `op(...)`.
+
+## Dropout
+
+::: tileops.ops.dropout.DropoutFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]

docs/api/index.md

@@ -14,22 +14,26 @@ d = op(a, b)                         # the specialized kernel is built on first
 ```
 
 The pages are ordered along the stack a caller works through: the dense matmul first,
-then attention and its linear replacements, then the elementwise and reduction
-primitives, then FFT.
+then attention, its position encodings and its linear replacements, then the
+elementwise and reduction primitives, then the convolutional family and FFT.
 
 | Page | What it covers |
 | --- | --- |
 | [GEMM](linear-algebra.md) | dense matmul — plain, batched, and the fp8 variants |
 | [Attention](attention.md) | forward and backward attention, including the paged and decode kernels |
+| [RoPE](rope.md) | rotary position embedding — NeoX and interleaved layouts, Llama 3.1, YaRN, LongRoPE |
 | [Linear Attention](linear-attention.md) | the linear-attention family: DeltaNet, GLA, KDA, and their kin |
 | [Mamba](mamba.md) | the SSD scan, its decode step, and the chunked forms |
 | [MHC](mhc.md) | multi-head compression |
 | [Normalization](normalization.md) | RMSNorm, LayerNorm, GroupNorm, BatchNorm and the fused variants |
 | [Elementwise](elementwise.md) | unary and binary maps, activations, and the in-place forms |
 | [Reduction](reduction.md) | sums, extrema, arg-reductions, cumulative scans, softmax |
+| [Convolution](convolution.md) | forward convolution over 1D, 2D and 3D inputs |
+| [Pooling](pool.md) | average, max and adaptive pooling, with and without indices |
+| [Dropout](dropout.md) | dropout with deterministic replay |
 | [FFT](fft.md) | the discrete transform |
-| [Quantization](quantization.md) | fp8 quantization — interface not yet stable |
-| [Top-k](topk.md) | top-k selection — interface not yet stable |
+| [Quantization](quantization.md) | fp8 quantization |
+| [Top-k](topk.md) | top-k selection |
 | [Trace](trace.md) | the in-kernel timeline tracer, a tool rather than an op |
 
 Two things this reference does not carry:

docs/api/pool.md

@@ -0,0 +1,84 @@
+# Pooling Operators
+
+Every op on this page is used the same way: construct it once, then call it. The
+constructor takes what the kernel is compiled with; the call takes the tensors.
+Both are documented under each op — `__init__` and `forward`, where `forward` is
+what runs when you call `op(...)`.
+
+## Average pooling
+
+::: tileops.ops.pool.AvgPool1dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.AvgPool2dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.AvgPool3dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+## Max pooling
+
+::: tileops.ops.pool.MaxPool1dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.MaxPool1dIndicesFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.MaxPool2dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.MaxPool2dIndicesFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.MaxPool3dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.MaxPool3dIndicesFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+## Adaptive pooling
+
+::: tileops.ops.pool.AdaptiveAvgPool2dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.AdaptiveMaxPool2dFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.pool.AdaptiveMaxPool2dIndicesFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]

docs/api/quantization.md

@@ -1,6 +1,14 @@
-# Quantization
+# Quantization Operators
 
-!!! note "Coming soon"
-    The `tileops.ops.fp8_quant` module is under active development in
-    [`tile-ai/TileOPs`](https://github.com/tile-ai/TileOPs) and will be
-    documented here once the public interface stabilizes.
+Every op on this page is used the same way: construct it once, then call it. The
+constructor takes what the kernel is compiled with; the call takes the tensors.
+Both are documented under each op — `__init__` and `forward`, where `forward` is
+what runs when you call `op(...)`.
+
+## FP8 quantization
+
+::: tileops.ops.fp8_quant.FP8QuantFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]

docs/api/rope.md

@@ -0,0 +1,48 @@
+# RoPE Operators
+
+Every op on this page is used the same way: construct it once, then call it. The
+constructor takes what the kernel is compiled with; the call takes the tensors.
+Both are documented under each op — `__init__` and `forward`, where `forward` is
+what runs when you call `op(...)`.
+
+## NeoX layout
+
+::: tileops.ops.rope.RopeNeoxFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.rope.RopeNeoxPositionIdsFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+## Interleaved layout
+
+::: tileops.ops.rope.RopeNonNeoxFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+## Scaled frequencies
+
+::: tileops.ops.rope.RopeLlama31FwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.rope.RopeYarnFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]
+
+::: tileops.ops.rope.RopeLongRopeFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]

docs/api/topk.md

@@ -1,6 +1,14 @@
-# Top-k
+# Top-k Operators
 
-!!! note "Coming soon"
-    The `tileops.ops.topk_selector` module is under active development in
-    [`tile-ai/TileOPs`](https://github.com/tile-ai/TileOPs) and will be
-    documented here once the public interface stabilizes.
+Every op on this page is used the same way: construct it once, then call it. The
+constructor takes what the kernel is compiled with; the call takes the tensors.
+Both are documented under each op — `__init__` and `forward`, where `forward` is
+what runs when you call `op(...)`.
+
+## Top-k selection
+
+::: tileops.ops.topk_selector.TopkSelectorFwdOp
+    options:
+      show_root_heading: true
+      heading_level: 3
+      members: ["__init__", "forward"]

mkdocs.yml

@@ -37,19 +37,23 @@ nav:
     - Using torch.compile: torch-compile.md
     - Adding a Backend: backends.md
   # Ordered along the stack a reader is working through: the dense matmul, then
-  # attention and its linear replacements, then the elementwise and reduction
-  # primitives, then FFT. The two pages still awaiting a stable interface sit
-  # after those, and Trace last — it is a tool, not an op family.
+  # attention, its position encodings and its linear replacements, then the
+  # elementwise and reduction primitives, then the convolutional family, then
+  # FFT, quantization and top-k, and Trace last — it is a tool, not an op family.
   - API Reference:
     - api/index.md
     - GEMM: api/linear-algebra.md
     - Attention: api/attention.md
+    - RoPE: api/rope.md
     - Linear Attention: api/linear-attention.md
     - Mamba: api/mamba.md
     - MHC: api/mhc.md
     - Normalization: api/normalization.md
     - Elementwise: api/elementwise.md
     - Reduction: api/reduction.md
+    - Convolution: api/convolution.md
+    - Pooling: api/pool.md
+    - Dropout: api/dropout.md
     - FFT: api/fft.md
     - Quantization: api/quantization.md
     - Top-k: api/topk.md
@@ -156,6 +160,10 @@ plugins:
             GEMM: GEMM
             Quantization: Quantization
             Attention: Attention
+            RoPE: RoPE
+            Convolution: Convolution
+            Pooling: Pooling
+            Dropout: Dropout
             Linear Attention: Linear Attention
             Mamba: Mamba
             FFT: FFT