forked from
anil.recoil.org/monopam-myspace
My aggregated monorepo of OCaml code, automaintained
Fix odoc doc build warnings: Tsig_include annotation, onnxrt refs, fatal warnings
- Fix typedtree_traverse Tsig_include to record ModuleType instead of Module,
resolving Stdlib.Hashtbl.HashedType resolution failure in compile-impl
- Qualify unresolved doc references in onnxrt.mli (e.g. {!run} -> {!Session.run})
- Fix {!type-Tensor.location} disambiguation syntax to {!Tensor.type-location}
- Fix {v ... v} code block indentation in onnxrt.mli
- Enable fatal doc warnings in dune-workspace
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
+12
-11
+1
dune-workspace
+1
dune-workspace
+1
-1
odoc/src/loader/typedtree_traverse.cppo.ml
+1
-1
odoc/src/loader/typedtree_traverse.cppo.ml
+10
-10
onnxrt/lib/onnxrt.mli
+10
-10
onnxrt/lib/onnxrt.mli
···
72
72
{1 GPU tensors}
73
73
74
74
When using the WebGPU backend, tensors can reside on the GPU to avoid
75
-
CPU↔GPU transfers between chained inference calls. See {!Tensor.location},
75
+
CPU↔GPU transfers between chained inference calls. See {!Tensor.type-location},
76
76
{!Tensor.download}, and {!Session.create} with
77
77
[~preferred_output_location:`Gpu_buffer].
78
78
···
138
138
139
139
{2 Lifecycle}
140
140
141
-
Tensors obtained from {!Session.run} should be {!dispose}d when no longer
141
+
Tensors obtained from {!Session.run} should be {!Tensor.dispose}d when no longer
142
142
needed. For CPU tensors this is a hint to the garbage collector; for GPU
143
143
tensors it releases the underlying [GPUBuffer] and failure to dispose will
144
144
leak GPU memory.
···
147
147
148
148
When a session is configured with
149
149
[~preferred_output_location:`Gpu_buffer], output tensors reside on the GPU.
150
-
Their data is not accessible synchronously — use {!download} to transfer
150
+
Their data is not accessible synchronously — use {!Tensor.download} to transfer
151
151
to CPU, or pass them directly as input to another {!Session.run} call to
152
152
keep computation on the GPU. *)
153
153
module Tensor : sig
···
302
302
303
303
{2 Session lifecycle}
304
304
305
-
1. Create a session with {!create}, which loads the model, applies graph
305
+
1. Create a session with {!Session.create}, which loads the model, applies graph
306
306
optimizations, and partitions operators across execution providers.
307
-
2. Run inference with {!run}, passing named input tensors and receiving
307
+
2. Run inference with {!Session.run}, passing named input tensors and receiving
308
308
named output tensors.
309
-
3. Release with {!release} when done, to free model weights and any
309
+
3. Release with {!Session.release} when done, to free model weights and any
310
310
GPU resources.
311
311
312
312
{2 Warm-up}
313
313
314
314
When using WebGPU, compute shaders are compiled lazily on the first
315
-
{!run} call. The first inference will be significantly slower than
315
+
{!Session.run} call. The first inference will be significantly slower than
316
316
subsequent ones. Run a warm-up inference with dummy data after session
317
317
creation if latency matters.
318
318
319
319
{2 Thread safety}
320
320
321
-
Sessions do not support concurrent {!run} calls. Await each result before
321
+
Sessions do not support concurrent {!Session.run} calls. Await each result before
322
322
starting the next inference. *)
323
323
module Session : sig
324
324
(** An opaque inference session handle. *)
···
419
419
- [n]: use [n] threads (requires cross-origin isolation)
420
420
421
421
Multi-threading requires the page to be served with:
422
-
{v
422
+
{v
423
423
Cross-Origin-Opener-Policy: same-origin
424
424
Cross-Origin-Embedder-Policy: require-corp
425
-
v} *)
425
+
v} *)
426
426
427
427
val set_simd : bool -> unit
428
428
(** [set_simd enabled] enables or disables WASM SIMD. Defaults to [true]