diff --git a/index.bs b/index.bs
index a9d600b2..5c40f8ab 100644
--- a/index.bs
+++ b/index.bs
@@ -1666,11 +1666,11 @@ partial interface MLGraphBuilder {
let currentRecurrentBias = [];
for (let dir = 0; dir < numDirections; ++dir) {
- currentWeight.push(builder.squeeze(builder.slice(weight, [dir, 0, 0], [1, -1, -1]), { axes: [0] }));
- currentRecurrentWeight.push(builder.squeeze(builder.slice(recurrentWeight, [dir, 0, 0], [1, -1, -1]), { axes: [0] }));
- currentBias.push(options.bias ? (builder.squeeze(builder.slice(options.bias, [dir, 0], [1, -1]), { axes: [0] })) : null);
+ currentWeight.push(builder.squeeze(builder.slice(weight, [dir, 0, 0], [1, 3 * hidden_size, input_size]), { axes: [0] }));
+ currentRecurrentWeight.push(builder.squeeze(builder.slice(recurrentWeight, [dir, 0, 0], [1, 3 * hidden_size, hidden_size]), { axes: [0] }));
+ currentBias.push(options.bias ? (builder.squeeze(builder.slice(options.bias, [dir, 0], [1, 3 * hidden_size]), { axes: [0] })) : null);
currentRecurrentBias.push(options.recurrentBias ?
- (builder.squeeze(builder.slice(options.recurrentBias, [dir, 0], [1, -1]), { axes: [0] })) : null);
+ (builder.squeeze(builder.slice(options.recurrentBias, [dir, 0], [1, 3 * hidden_size]), { axes: [0] })) : null);
}
for (let step = 0; step < steps; ++step) {
@@ -1678,12 +1678,12 @@ partial interface MLGraphBuilder {
let currentOutput = null;
for (let dir = 0; dir < numDirections; ++dir) {
- currentHidden.push(builder.squeeze(builder.slice(hiddenState, [dir, 0, 0], [1, -1, -1]), { axes: [0] }));
+ currentHidden.push(builder.squeeze(builder.slice(hiddenState, [dir, 0, 0], [1, batch_size, hidden_size]), { axes: [0] }));
}
for (let dir = 0; dir < numDirections; ++dir) {
let slice = (dir == 1 || options.direction == "backward" ? steps - step - 1 : step);
- let currentInput = builder.squeeze(builder.slice(input, [slice, 0, 0], [1, -1, -1]), { axes: [0] });
+ let currentInput = builder.squeeze(builder.slice(input, [slice, 0, 0], [1, batch_size, input_size]), { axes: [0] });
let result = builder.reshape(
builder.gruCell(
@@ -1758,11 +1758,11 @@ partial interface MLGraphBuilder {
builder.add(
builder.matmul(
input,
- builder.transpose(builder.slice(weight, [0, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(weight, [0, 0], [hiddenSize, input_size]))
),
builder.matmul(
hiddenState,
- builder.transpose(builder.slice(recurrentWeight, [0, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(recurrentWeight, [0, 0], [hiddenSize, hidden_size]))
)
)
)
@@ -1778,11 +1778,11 @@ partial interface MLGraphBuilder {
builder.add(
builder.matmul(
input,
- builder.transpose(builder.slice(weight, [hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(weight, [hiddenSize, 0], [hiddenSize, input_size]))
),
builder.matmul(
hiddenState,
- builder.transpose(builder.slice(recurrentWeight, [hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(recurrentWeight, [hiddenSize, 0], [hiddenSize, hidden_size]))
)
)
)
@@ -1797,7 +1797,7 @@ partial interface MLGraphBuilder {
builder.add(
builder.matmul(
input,
- builder.transpose(builder.slice(weight, [2 * hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(weight, [2 * hiddenSize, 0], [hiddenSize, input_size]))
),
builder.mul(
r,
@@ -1805,7 +1805,7 @@ partial interface MLGraphBuilder {
(options.recurrentBias ? builder.slice(options.recurrentBias, [2 * hiddenSize], [hiddenSize]) : zero),
builder.matmul(
hiddenState,
- builder.transpose(builder.slice(recurrentWeight, [2 * hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(recurrentWeight, [2 * hiddenSize, 0], [hiddenSize, hidden_size]))
)
)
)
@@ -1823,11 +1823,11 @@ partial interface MLGraphBuilder {
builder.add(
builder.matmul(
input,
- builder.transpose(builder.slice(weight, [2 * hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(weight, [2 * hiddenSize, 0], [hiddenSize, input_size]))
),
builder.matmul(
builder.mul(r, hiddenState),
- builder.transpose(builder.slice(recurrentWeight, [2 * hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(recurrentWeight, [2 * hiddenSize, 0], [hiddenSize, hidden_size]))
)
)
)
@@ -2121,13 +2121,13 @@ partial interface MLGraphBuilder {
let currentPeepholeWeight = [];
for (let dir = 0; dir < numDirections; ++dir) {
- currentWeight.push(builder.squeeze(builder.slice(weight, [dir, 0, 0], [1, -1, -1]), { axes: [0] }));
- currentRecurrentWeight.push(builder.squeeze(builder.slice(recurrentWeight, [dir, 0, 0], [1, -1, -1]), { axes: [0] }));
- currentBias.push(options.bias ? (builder.squeeze(builder.slice(options.bias, [dir, 0], [1, -1]), { axes: [0] })) : null);
+ currentWeight.push(builder.squeeze(builder.slice(weight, [dir, 0, 0], [1, 4 * hidden_size, input_size]), { axes: [0] }));
+ currentRecurrentWeight.push(builder.squeeze(builder.slice(recurrentWeight, [dir, 0, 0], [1, 4 * hidden_size, hidden_size]), { axes: [0] }));
+ currentBias.push(options.bias ? (builder.squeeze(builder.slice(options.bias, [dir, 0], [1, 4 * hidden_size]), { axes: [0] })) : null);
currentRecurrentBias.push(options.recurrentBias ?
- (builder.squeeze(builder.slice(options.recurrentBias, [dir, 0], [1, -1]), { axes: [0] })) : null);
+ (builder.squeeze(builder.slice(options.recurrentBias, [dir, 0], [1, 4 * hidden_size]), { axes: [0] })) : null);
currentPeepholeWeight.push(options.peepholeWeight ?
- (builder.squeeze(builder.slice(options.peepholeWeight, [dir, 0], [1, -1]), { axes: [0] })) : null);
+ (builder.squeeze(builder.slice(options.peepholeWeight, [dir, 0], [1, 4 * hidden_size]), { axes: [0] })) : null);
}
for (let step = 0; step < steps; ++step) {
@@ -2137,13 +2137,13 @@ partial interface MLGraphBuilder {
let nextCell = null;
for (let dir = 0; dir < numDirections; ++dir) {
- currentHidden.push(builder.squeeze(builder.slice(hiddenState, [dir, 0, 0], [1, -1, -1]), { axes: [0] }));
- currentCell.push(builder.squeeze(builder.slice(cellState, [dir, 0, 0], [1, -1, -1]), { axes: [0] }));
+ currentHidden.push(builder.squeeze(builder.slice(hiddenState, [dir, 0, 0], [1, batch_size, hidden_size]), { axes: [0] }));
+ currentCell.push(builder.squeeze(builder.slice(cellState, [dir, 0, 0], [1, batch_size, hidden_size]), { axes: [0] }));
}
for (let dir = 0; dir < numDirections; ++dir) {
let slice = (dir == 1 || options.direction == "backward" ? steps - step - 1 : step);
- let currentInput = builder.squeeze(builder.slice(input, [slice, 0, 0], [1, -1, -1]), { axes: [0] });
+ let currentInput = builder.squeeze(builder.slice(input, [slice, 0, 0], [1, batch_size, input_size]), { axes: [0] });
let results = builder.lstmCell(
currentInput, currentWeight[dir], currentRecurrentWeight[dir],
@@ -2227,11 +2227,11 @@ partial interface MLGraphBuilder {
builder.add(
builder.matmul(
input,
- builder.transpose(builder.slice(weight, [0, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(weight, [0, 0], [hiddenSize, input_size]))
),
builder.matmul(
hiddenState,
- builder.transpose(builder.slice(recurrentWeight, [0, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(recurrentWeight, [0, 0], [hiddenSize, hidden_size]))
)
)
)
@@ -2253,11 +2253,11 @@ partial interface MLGraphBuilder {
builder.add(
builder.matmul(
input,
- builder.transpose(builder.slice(weight, [2 * hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(weight, [2 * hiddenSize, 0], [hiddenSize, input_size]))
),
builder.matmul(
hiddenState,
- builder.transpose(builder.slice(recurrentWeight, [2 * hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(recurrentWeight, [2 * hiddenSize, 0], [hiddenSize, hidden_size]))
)
)
)
@@ -2274,11 +2274,11 @@ partial interface MLGraphBuilder {
builder.add(
builder.matmul(
input,
- builder.transpose(builder.slice(weight, [3 * hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(weight, [3 * hiddenSize, 0], [hiddenSize, input_size]))
),
builder.matmul(
hiddenState,
- builder.transpose(builder.slice(recurrentWeight, [3 * hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(recurrentWeight, [3 * hiddenSize, 0], [hiddenSize, hidden_size]))
)
)
)
@@ -2299,11 +2299,11 @@ partial interface MLGraphBuilder {
builder.add(
builder.matmul(
input,
- builder.transpose(builder.slice(weight, [hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(weight, [hiddenSize, 0], [hiddenSize, input_size]))
),
builder.matmul(
hiddenState,
- builder.transpose(builder.slice(recurrentWeight, [hiddenSize, 0], [hiddenSize, -1]))
+ builder.transpose(builder.slice(recurrentWeight, [hiddenSize, 0], [hiddenSize, hidden_size]))
)
)
)
@@ -2690,23 +2690,15 @@ partial interface MLGraphBuilder {
### The slice() method ### {#api-mlgraphbuilder-slice}
Produce a slice of the input tensor.
**Arguments:**
- *input*: an {{MLOperand}}. The input tensor.
- - *starts*: a sequence of {{long}}. The starting indices to slice of the corresponding axes of the input shape. A negative index value is interpreted as counting back from the end. For example, the value -1
- - *sizes*: a sequence of {{long}}. The lengths to slice of the corresponding axes of the input shape.
- The length value of -1 selects all the remaining elements from the starting index of the given axis.
- - *options*: an optional {{MLSliceOptions}}. The optional parameters of the operation.
- - *axes*: a sequence of {{unsigned long}}. The dimensions of the input shape to which *starts* and *sizes* apply. The values in the sequence must be in the range [0, N-1] where N is the rank of input tensor. When not specified, the sequence is assumed to be [0, ..., N-1], e.g. [0,1,2] for a 3-D tensor.
+ - *starts*: a sequence of {{unsigned long}}. The sequence of unsigned integer values indicating the starting index to slice of each input dimension, of length N where N is the rank of the input tensor. For each dimension *d* of *input*, *starts[d]* indicates the starting index to slice in that dimension. The starting index must be in the range [0, input size - 1] in that dimension.
+ - *sizes*: a sequence of {{unsigned long}}. The sequence of unsigned integer values indicating the number of elements to slice of each input dimension, of length N where N is the rank of the input tensor. For each dimension *d* of *input*, *sizes[d]* indicates the number of elements to slice in that dimension. The size must not be 0 and must satisfy the constraint *starting index + size <= input size* in that dimension.
**Returns:** an {{MLOperand}}. The output tensor of the same rank as the input tensor with tensor values stripped to the specified starting and ending indices in each dimension.
@@ -2839,9 +2831,13 @@ partial interface MLGraphBuilder {
// This sample shows the case that the splits parameter is an array.
const outputs = [];
+ let starts = Array(input_rank).fill(0);
+ let sizes = input_shape;
let start = 0;
for (const size of splits) {
- outputs.push(builder.slice(input, [start], [size], { axes: [options.axis] }));
+ starts[options.axis] = start;
+ sizes[options.axis] = size;
+ outputs.push(builder.slice(input, starts, sizes));
start += size;
}
return outputs;