fix: drop support for Sampler

lib/binding.ts

@@ -7,9 +7,6 @@ interface Binding {
   moduleExecute(ptr: ExternalObject, method_name: string, inputs: InternalEValue[]): Promise<InternalEValue[]>;
   moduleGetMethodMeta(ptr: ExternalObject, method_name: string): MethodMeta;
   moduleMethodNames(ptr: ExternalObject): string[];
-  // sampler methods
-  createSampler(vocab_size: number, temperature: number, top_p: number, seed: number): ExternalObject;
-  samplerSample(ptr: ExternalObject, tensor: ExternalObject): number;
   // tensor methods
   createTensor(dtype: DType, shape: number[], data: ArrayBuffer): ExternalObject;
   tensorGetDtype(ptr: ExternalObject): DType;

lib/index.ts

@@ -170,33 +170,4 @@ class Module {
   }
 }
 
-class Sampler {
-  _ptr: ExternalObject;
-  _vocab_size: number;
-
-  constructor(vocab_size: number, temperature: number = 0.7, topP: number = 0.9, seed?: number) {
-    this._vocab_size = vocab_size;
-    this._ptr = mod.createSampler(
-      vocab_size,
-      temperature,
-      topP,
-      seed ?? Math.floor(Math.random() * 1000000)
-    );
-  }
-
-  sample(tensor: Tensor): number {
-    if (tensor.dtype !== "float32") {
-      throw new Error(`Unsupported dtype: ${tensor.dtype}`);
-    }
-    if (tensor.shape.length !== 3 || tensor.shape[0] !== 1 || tensor.shape[1] === 0 || tensor.shape[2] !== this._vocab_size) {
-      throw new Error(`Invalid shape: ${tensor.shape}`);
-    }
-    return mod.samplerSample(this._ptr, tensor._ptr);
-  }
-
-  dispose() {
-    delete this._ptr;
-  }
-}
-
-export { Sampler, Tensor, Module };
+export { Tensor, Module };

src/lib.rs

@@ -4,17 +4,13 @@ mod evalue_tag;
 mod macros;
 mod method_meta;
 mod module;
-mod sampler;
 mod tensor;
 mod tensor_type;
 
 use neon::prelude::*;
 
 #[neon::main]
 fn main(mut cx: ModuleContext) -> NeonResult<()> {
-    // Sampler
-    cx.export_function("createSampler", sampler::create)?;
-    cx.export_function("samplerSample", sampler::sample)?;
     // Tensor
     cx.export_function("createTensor", tensor::create)?;
     cx.export_function("tensorGetDtype", tensor::get_dtype)?;