tensorlogic-trustformers 0.1.0-beta.1

Transformer-as-rules: Self-attention and FFN layers as einsum expressions
Documentation
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[package]
edition = "2021"
name = "tensorlogic-trustformers"
version = "0.1.0-beta.1"
build = false
autolib = false
autobins = false
autoexamples = false
autotests = false
autobenches = false
description = "Transformer-as-rules: Self-attention and FFN layers as einsum expressions"
homepage = "https://github.com/cool-japan/tensorlogic"
readme = "README.md"
license = "Apache-2.0"
repository = "https://github.com/cool-japan/tensorlogic"

[lib]
name = "tensorlogic_trustformers"
path = "src/lib.rs"

[[example]]
name = "01_basic_encoder"
path = "examples/01_basic_encoder.rs"

[[example]]
name = "02_trustformers_integration"
path = "examples/02_trustformers_integration.rs"

[[example]]
name = "03_rule_based_attention"
path = "examples/03_rule_based_attention.rs"

[[example]]
name = "04_sparse_attention"
path = "examples/04_sparse_attention.rs"

[[example]]
name = "05_gradient_checkpointing"
path = "examples/05_gradient_checkpointing.rs"

[[example]]
name = "06_kv_cache_inference"
path = "examples/06_kv_cache_inference.rs"

[[example]]
name = "07_vision_transformers"
path = "examples/07_vision_transformers.rs"

[[example]]
name = "08_mixture_of_experts"
path = "examples/08_mixture_of_experts.rs"

[[example]]
name = "09_modern_llm_optimizations"
path = "examples/09_modern_llm_optimizations.rs"

[[example]]
name = "10_modern_llm_complete"
path = "examples/10_modern_llm_complete.rs"

[[bench]]
name = "model_benchmarks"
path = "benches/model_benchmarks.rs"
harness = false

[dependencies.anyhow]
version = "1"

[dependencies.scirs2-core]
version = "0.1.3"

[dependencies.serde]
version = "1"
features = [
    "derive",
    "derive",
]

[dependencies.serde_json]
version = "1"

[dependencies.tensorlogic-infer]
version = "0.1.0-beta.1"

[dependencies.tensorlogic-ir]
version = "0.1.0-beta.1"

[dependencies.thiserror]
version = "2"

[dev-dependencies.approx]
version = "0.5"

[dev-dependencies.criterion]
version = "0.8"
features = ["html_reports"]