Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix #713: DOMString to USVString #715

Merged
merged 1 commit into from
Jul 5, 2024
Merged

Fix #713: DOMString to USVString #715

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 7 additions & 7 deletions index.bs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -801,7 +801,7 @@ The <dfn dfn-for=MLContextOptions dfn-type=dict-member>powerPreference</dfn> opt
The {{MLContext}} interface represents a global state of neural network compute workload and execution processes. Each {{MLContext}} object has associated [=context type=], {{MLDeviceType}} and {{MLPowerPreference}}.

<script type=idl>
typedef record<DOMString, ArrayBufferView> MLNamedArrayBufferViews;
typedef record<USVString, ArrayBufferView> MLNamedArrayBufferViews;

dictionary MLComputeResult {
MLNamedArrayBufferViews inputs;
Expand Down Expand Up @@ -997,11 +997,11 @@ interface MLGraph {};
::
The context of type {{MLContext}} associated with this {{MLGraph}}.

: <dfn>\[[inputDescriptors]]</dfn> of type [=record=]&lt;{{DOMString}}, {{MLOperandDescriptor}}&gt;
: <dfn>\[[inputDescriptors]]</dfn> of type [=record=]&lt;{{USVString}}, {{MLOperandDescriptor}}&gt;
::
Maps the name of an input {{MLOperand}} to its {{MLOperandDescriptor}} for all input {{MLOperand}}s of this {{MLGraph}}.

: <dfn>\[[outputDescriptors]]</dfn> of type [=record=]&lt;{{DOMString}}, {{MLOperandDescriptor}}&gt;
: <dfn>\[[outputDescriptors]]</dfn> of type [=record=]&lt;{{USVString}}, {{MLOperandDescriptor}}&gt;
::
Maps the name of an output {{MLOperand}} to its {{MLOperandDescriptor}} for all output {{MLOperand}}s of this {{MLGraph}}.

Expand Down Expand Up @@ -1233,15 +1233,15 @@ To <dfn for="MLGraphBuilder">validate activation</dfn> given {{MLGraphBuilder}}
The {{MLGraphBuilder}} interface defines a set of operations as identified by the [[#usecases]] that can be composed into a computational graph. It also represents the intermediate state of a graph building session.

<script type=idl>
typedef record<DOMString, MLOperand> MLNamedOperands;
typedef record<USVString, MLOperand> MLNamedOperands;

[SecureContext, Exposed=(Window, DedicatedWorker)]
interface MLGraphBuilder {
// Construct the graph builder from the context.
constructor(MLContext context);

// Create an operand for a graph input.
MLOperand input(DOMString name, MLOperandDescriptor descriptor);
MLOperand input(USVString name, MLOperandDescriptor descriptor);

// Create an operand for a graph constant.
MLOperand constant(MLOperandDescriptor descriptor, ArrayBufferView bufferView);
Expand Down Expand Up @@ -2262,7 +2262,7 @@ partial interface MLGraphBuilder {
</details>

### Element-wise logical operations ### {#api-mlgraphbuilder-logical}
Compare input tensors element-wise and return a uint8 tensor of values 0 or 1 for the comparisons. For single-operand operations, return the logical results of the operation.
Compare input tensors element-wise and return a uint8 tensor of values 0 or 1 for the comparisons. For single-operand operations, return the logical results of the operation.

The input tensor will be broadcasted according to [[!numpy-broadcasting-rule]]. The [=MLOperand/rank=] of the output tensor is the maximum
[=MLOperand/rank=] of the input tensors.
Expand Down Expand Up @@ -3686,7 +3686,7 @@ partial interface MLGraphBuilder {
The N-D tensor of the bias values whose shape is determined by the |axes| member in that each value in |axes| indicates the dimension of the input tensor with bias values. For example, for an |axes| values of [1,2,3], the shape of this tensor is the list of the corresponding sizes of the input dimension 1, 2 and 3. When this member is not present, the bias value is assumed to be 0.

: <dfn>axes</dfn>
::
::
The indices to the input dimensions to reduce. When this member is not present, it is treated as if all dimensions except the first were given (e.g. for a 4-D input tensor, axes = [1,2,3]). That is, the reduction for the mean and variance values are calculated across all the input features for each independent batch. If empty, no dimensions are reduced.
: <dfn>epsilon</dfn>
::
Expand Down