completed lstm

src/arg_max_min.js

@@ -2,7 +2,8 @@
 
 import {Tensor, sizeOfShape} from './lib/tensor.js';
 import {reduceMax, reduceMin, selectValuesToReduce} from './reduce.js';
-import {squeeze} from './squeeze.js';
+import {squeeze} from './reshape.js';
+
 
 /**
  * Get the index location of the minimum or maxmium values of all the input values along the axes.

src/gru.js

@@ -2,11 +2,10 @@
 
 import {concat} from './concat.js';
 import {gruCell} from './gru_cell.js';
-import {reshape} from './reshape.js';
+import {reshape, squeeze} from './reshape.js';
 import {sizeOfShape, Tensor} from './lib/tensor.js';
 import {sigmoid} from './sigmoid.js';
 import {slice} from './slice.js';
-import {squeeze} from './squeeze.js';
 import {tanh} from './tanh.js';
 import {validateGruParams} from './lib/validate-input.js';
 

src/lstm.js

@@ -2,11 +2,10 @@
 
 import {concat} from './concat.js';
 import {lstmCell} from './lstm_cell.js';
-import {reshape} from './reshape.js';
+import {reshape, squeeze} from './reshape.js';
 import {sizeOfShape, Tensor} from './lib/tensor.js';
 import {sigmoid} from './sigmoid.js';
 import {slice} from './slice.js';
-import {squeeze} from './squeeze.js';
 import {tanh} from './tanh.js';
 import {validateLstmParams} from './lib/validate-input.js';
 

src/reduce.js

@@ -1,7 +1,7 @@
 'use strict';
 
 import {pow} from './binary.js';
-import {squeeze} from './squeeze.js';
+import {squeeze} from './reshape.js';
 import {abs, exp, log} from './unary.js';
 import {sizeOfShape, Scalar, Tensor} from './lib/tensor.js';
 import {validateReduceParams} from './lib/validate-input.js';

src/reshape.js

@@ -1,6 +1,7 @@
 'use strict';
 
 import {Tensor, sizeOfShape} from './lib/tensor.js';
+import {validateSqueezeParams} from './lib/validate-input.js';
 
 /**
  * Alter the shape of a tensor to a new shape.
@@ -31,3 +32,19 @@ export function reshape(input, newShape) {
   const output = new Tensor(outputShape, input.data);
   return output;
 }
+
+/**
+ * Reduce the rank of a tensor by eliminating dimensions with size 1 of the tensor shape.
+ * @param {Tensor} input
+ * @param {MLSqueezeOptions} options
+ * @return {Tensor}
+ */
+export function squeeze(input, {axes} = {}) {
+  validateSqueezeParams(...arguments);
+  const inpAxes = axes ?? new Array(input.rank).fill(0).map((_, i) => i);
+
+  const outputShape = input.shape.filter((dim, axis) =>
+    !(dim === 1 && inpAxes.indexOf(axis) !== -1));
+  const output = reshape(input, outputShape);
+  return output;
+}