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TensorFlow 0.1.3: context-bound constants and default transpose
Stamp dtype/rank/device facts on OwnedTensorHandle after full boundary or operation-result validation, then reuse them for later typed checks of the same resident intermediate inside one generated call graph. Core API 1.6 has no per-function prologue hook, so reuse stays value-carried (no global or thread-local tensor cache). TF_Status remains per-operation without a public TF_ResetStatus. CUDA derivation preserves the facts short-circuit and GPU:0 device path. Add source contracts plus real-Cargo intermediate-chain and small-batch scoring equivalence coverage.
Record delivered scope, non-claims, Core prologue-hook limitation, per-op TF_Status rationale, and the small-batch equivalence command/interpretation for the Unreleased 0.1.3 candidate.
Assert each of the three small_batch generated pyfunction bodies contains for round_idx in 0..4 and the scalar rem-if branch, scoped per function so unrelated loops elsewhere cannot satisfy the contract.
feat: 0.1.3 invocation-local reuse and small-batch scoring equivalence
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Summary
ABI and CUDA boundaries
This remains an owned thin wrapper over the pinned TensorFlow TFE C API and private EagerTensor bridge, not a pure-Rust TensorFlow implementation or stable ABI promise. The CUDA E3 lane remains build-only and non-certifying with
support_claim=false,certification_ready=false,kernel_activity_verified=false, andruntime_transfer_profiled=false.Verification
git diff --checkpassedTagging and PyPI upload occur only after this PR is green and merged.