bulk change to unify **Required.** and **Optional.** (#6503)
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20f10a43a4
@@ -23,7 +23,7 @@ declared in `variable_id` and returns an error otherwise.
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**Inputs**
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* **1**: `new_value` - input tensor of any supported type. **Required**.
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* **1**: `new_value` - input tensor of any supported type. **Required.**
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**Outputs**
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@@ -4,7 +4,7 @@
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**Category**: Infrastructure
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**Short description**: *Loop* operation performs recurrent execution of the network, which is described in the `body`, iterating through the data.
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**Short description**: *Loop* operation performs recurrent execution of the network, which is described in the `body`, iterating through the data.
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The operation has similar semantic to the ONNX* Loop [operation](https://github.com/onnx/onnx/blob/master/docs/Changelog.md#Loop-13).
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**Detailed description**
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@@ -20,21 +20,21 @@ There are several combinations of these two inputs `(trip_count, execution condi
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```
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input (-1, true) // infinite loop
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bool cond = true;
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for (int i = 0; cond; ++i)
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for (int i = 0; cond; ++i)
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{
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cond = true; // sub-graph calculating condition must always return "true"!
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}
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input (-1, cond) // while loop
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bool cond = ...;
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for (int i = 0; cond; ++i)
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for (int i = 0; cond; ++i)
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{
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cond = ...;
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}
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input (-1, true) // do-while loop
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bool cond = true;
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for (int i = 0; cond; ++i)
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for (int i = 0; cond; ++i)
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{
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cond = ...;
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}
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@@ -42,7 +42,7 @@ There are several combinations of these two inputs `(trip_count, execution condi
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input (trip_count, true) // for loop
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int trip_count = ...;
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bool cond = true;
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for (int i = 0; i < trip_count; ++i)
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for (int i = 0; i < trip_count; ++i)
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{
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cond = true; // sub-graph calculating condition must always return "true"!
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}
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@@ -50,7 +50,7 @@ There are several combinations of these two inputs `(trip_count, execution condi
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input (trip_count, cond) // for with condition
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int trip_count = ...;
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bool cond = ...;
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for (int i = 0; i < trip_count && cond; ++i)
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for (int i = 0; i < trip_count && cond; ++i)
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{
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cond = ...;
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}
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@@ -133,11 +133,11 @@ Loop operation description in the IR also has several special sections: `body`,
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**Loop Inputs**
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* **Trip count**: A scalar or 1D tensor with 1 element of `int64` or `int32` type specifying maximum number of iterations. *Required*.
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* **Trip count**: A scalar or 1D tensor with 1 element of `int64` or `int32` type specifying maximum number of iterations. **Required.**
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* **ExecutionCondition**: A scalar or 1D tensor with 1 element of `boolean` type specifying whether to execute the first iteration or not. `True` value means to execute the 1st iteration. *Required*.
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* **ExecutionCondition**: A scalar or 1D tensor with 1 element of `boolean` type specifying whether to execute the first iteration or not. `True` value means to execute the 1st iteration. **Required.**
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* **Multiple other inputs**: tensors of different types and shapes. *Optional*.
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* **Multiple other inputs**: tensors of different types and shapes. **Optional.**
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**Loop Outputs**
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@@ -146,12 +146,12 @@ Loop operation description in the IR also has several special sections: `body`,
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**Body Inputs**
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* **Multiple inputs**: tensors of different types and shapes except the one corresponding to the current iteration number. This input is marked in the port_map with attribute `purpose = "current_iteration"` and produces a scalar or 1D tensor with 1 element of `int64` or `int32` type. *Optional*.
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* **Multiple inputs**: tensors of different types and shapes except the one corresponding to the current iteration number. This input is marked in the port_map with attribute `purpose = "current_iteration"` and produces a scalar or 1D tensor with 1 element of `int64` or `int32` type. **Optional.**
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**Body Outputs**
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* **Multiple outputs**: Results of execution of the `body`. Tensors of any type and shape except the one corresponding to the output with execution condition. This output is marked in the port_map with attribute `purpose = "execution_condition"` and is mandatory and produces a scalar or 1D tensor with 1 element of `boolean` type. Other outputs are optional.
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* **Multiple outputs**: Results of execution of the `body`. Tensors of any type and shape except the one corresponding to the output with execution condition. This output is marked in the port_map with attribute `purpose = "execution_condition"` and is mandatory and produces a scalar or 1D tensor with 1 element of `boolean` type. Other outputs are optional.
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**Examples**
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@@ -25,7 +25,7 @@ with the shape and type from the 1 input.
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**Inputs**
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* **1**: `init_value` - input tensor with constant values of any supported type. **Required**.
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* **1**: `init_value` - input tensor with constant values of any supported type. **Required.**
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**Outputs**
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