Learning.measurable_step🔗

This page has the declaration's own card below, then its dependency graph, then a card for each dependency (type dependencies first, then the rest of the transitive closure). For a theorem, the graph and the dependency cards only follow its statement's dependencies (its proof is replaced by sorry, so what it proves doesn't depend on how); for everything else, both the type and the body/value are followed, since their content is part of what later declarations build on.

Minimal Lean file

Learning.measurable_step.{u_1, u_2, u_3} {𝓐 : Type u_1} {𝓨 : Type u_2}
  {Ω : Type u_3} {m𝓐 : MeasurableSpace 𝓐} {m𝓨 : MeasurableSpace 𝓨}
  {mΩ : MeasurableSpace Ω} {A : ℕ → Ω → 𝓐} {Y : ℕ → Ω → 𝓨} (n : ℕ)
  (hA : Measurable (A n)) (hY : Measurable (Y n)) :
  Measurable (step A Y n)
Learning.measurable_step.{u_1, u_2, u_3}
  {𝓐 : Type u_1} {𝓨 : Type u_2}
  {Ω : Type u_3} {m𝓐 : MeasurableSpace 𝓐}
  {m𝓨 : MeasurableSpace 𝓨}
  {mΩ : MeasurableSpace Ω} {A : ℕ → Ω → 𝓐}
  {Y : ℕ → Ω → 𝓨} (n : ℕ)
  (hA : Measurable (A n))
  (hY : Measurable (Y n)) :
  Measurable (step A Y n)

lemma measurable_step (n : ℕ) (hA : Measurable (A n)) (hY : Measurable (Y n)) :
    Measurable (step A Y n)

by
  unfold step
  fun_prop

Dependency graph

Type dependencies (1)

Learning.step.{u_1, u_2, u_3} {𝓐 : Type u_1} {𝓨 : Type u_2}
  {Ω : Type u_3} (A : ℕ → Ω → 𝓐) (Y : ℕ → Ω → 𝓨) (n : ℕ) (ω : Ω) : 𝓐 × 𝓨
Learning.step.{u_1, u_2, u_3}
  {𝓐 : Type u_1} {𝓨 : Type u_2}
  {Ω : Type u_3} (A : ℕ → Ω → 𝓐)
  (Y : ℕ → Ω → 𝓨) (n : ℕ) (ω : Ω) : 𝓐 × 𝓨

def step (A : ℕ → Ω → 𝓐) (Y : ℕ → Ω → 𝓨) (n : ℕ) (ω : Ω) : 𝓐 × 𝓨 :=
  (A n ω, Y n ω)