Initial import: grid-bot — grid trading bot for BTC-USDT on Cifra Markets
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# This yaml file contains all the possible tags that can be defined in `tags` in `native_functions.yaml`
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- tag: inplace_view
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desc: |
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This tag indicates if an operator *only* modifies the tensor metadata
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- tag: pt2_compliant_tag
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desc: |
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This tag indicates if the operator is guaranteed to
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work with the PT2 compilation APIs (torch.compile,
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torch.export, etc). If you add this tag to an
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operator, please use
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`torch.testing._internal.optest.opcheck` to test that
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the operator has been registered correctly and
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works with torch.compile
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- tag: view_copy
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desc: |
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This tag indicates operators that are *_copy* variants
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of view/aliasing operators. If an operator has a view_copy tag,
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then it should have the name {op}_copy, where {op} is a view operator.
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- tag: dynamic_output_shape
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desc: |
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This tag indicates if an operator's output's shape depends on input Tensor
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data.
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- tag: data_dependent_output
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desc: |
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Operator has a non-Tensor output whose value is dependent on the data
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of Tensor inputs. Among other things, this implies that this operator
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cannot be run with meta tensor (since data is not available), nor
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can it be symbolically traced.
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- tag: generated
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desc: |
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This tag indicates that the operator doesn't have an explicit entry in
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native_functions.yaml, and instead was generated automatically by the codegen.
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- tag: nondeterministic_seeded
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desc: |
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This tag indicates if an operator is nondeterministically seeded
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(i.e., is random) such that the operator intentionally produces
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different results when run twice on the same inputs, but this randomness
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is controlled by a Generator which, if reseeded would give you the
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same result.
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- tag: nondeterministic_bitwise
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desc: |
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This tag indicates if an operator doesn't guarantee bitwise equivalence
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across different runs of an operator with identical inputs.
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- tag: needs_exact_strides
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desc: |
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This tag indicates that the operator should be passed Tensors following
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the same strides as observed in eager when compiled in inductor.
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Only one of {needs_exact_strides, needs_contiguous_strides, needs_fixed_stride_order, flexible_layout}
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can apply; if multiple are assigned then we assume the most restrictive one.
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- tag: needs_contiguous_strides
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desc: |
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This tag indicates that the operator should be passed contiguous Tensors.
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Failure to do so will result in undefined behavior.
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- tag: needs_fixed_stride_order
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desc: |
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This tag indicates that the operator should be passed Tensors following
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the same stride permutation as observed in eager when compiled in inductor.
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Only one of {needs_exact_strides, needs_contiguous_strides, needs_fixed_stride_order, flexible_layout}
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can apply; if multiple are assigned then we assume the most restrictive one.
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- tag: flexible_layout
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desc: |
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This tag indicates that the custom operator can accept inputs with varying
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strides/storage_offset and that when compiled, Inductor is allowed to change
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the strides/storage_offset of inputs to the custom operator.
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Only one of {needs_exact_strides, needs_contiguous_strides, needs_fixed_stride_order, flexible_layout}
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can apply; if multiple are assigned then we assume the most restrictive one.
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# NOTE [Core ATen Ops]
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- tag: core
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desc: |
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Core aten ops is a subset of aten ops that remains after aten-to-aten decomposition and
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functionalization pass. Core aten ops are fully functional and adhere to single static
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assignment (SSA): this implies there will be no `inplace` or `_out` variants in this opset.
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This opset is designed to serve as the functional IR to interface with compiler backends.
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In contrast to primTorch, core aten opset doesn't decompose ops into explicit
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type promotion and broadcasting ops.
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Core aten ops is also effectively the opset produced by torchdynamo.export(aten_graph=True),
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and thus can be used as an opset for export purpose.
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- tag: pointwise
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desc: |
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Pointwise operators are operators where each element of the output is computed only by accessing
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the corresponding element of all the broadcasted inputs. The output shape will be the broadcasted
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shape of the inputs.
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- tag: maybe_aliasing_or_mutating
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desc: |
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For some ops, we can't statically determine whether the op is functional or not. Note that this is only
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relevant to CIA ops that decompose before functionalization/autograd. It is useful to
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know this information for export as we would want to decompose these ops as they are unsafe to be
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preserved.
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- tag: cudagraph_unsafe
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desc: |
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This operator does not support cudagraphs. The presence of this tag on an operator will cause
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Inductor to split the graph around this operator. Note that operators without this tag may still
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not support CUDAGraphs. Inductor may have other hardcoded lists around that.
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- tag: reduction
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desc: |
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This tag indicates that an operator performs a reduction operation, computing aggregate values
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(sum, mean, max, min, etc.) across one or more dimensions of the input tensor(s).
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- tag: out_variant
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desc: |
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This tag indicates that the operator is an out variant of a functional
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operator. This tag only applies to custom ops. Out variant operators
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write their results to pre-allocated output tensors (the out args)
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rather than allocating new tensors.
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